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Have you sat in a Management or Board Meeting of a company in the Business Services sector and thought: ‘how can we get more customers?’ Have you looked at the Marketing line in the annual budget and asked: ‘what would happen if we spent double or half this amount?’. There is no reason that your business shouldn’t be able to answer these questions just as well as the fastest growth ecommerce or VC-feted SaaS platform. When we work with Business Services clients – in categories ranging from accountancy firms to consultancies selling to investors to marketing agencies – we address these questions by talking about ‘Customer Acquisition’. Among the many potential levers available to accelerate customer acquisition, there are four that we find most effective for the Business Services sector, that we’d recommend as starting points for any investor or CEO: 1.       Define your ICP An Ideal Customer Profile (ICP) is a description of the customers that you would most like to acquire for your business. In other words, if one more customer walked in the office door (metaphorically), what do you want them to look like? The ICP is a more specific version of the long-used “target market” concept in marketing. The ICP, however, goes beyond demographic/firmographic information and can include customer problems, the triggers that have caused the customers to start considering a purchase, organizational structure, decision-making processes, and more. It should also consider the ‘personas’ you are targeting – the job titles and functional responsibilities of the key decision makers for your particular service offering. Both marketing and sales teams can use an ICP when setting up demand generation activities (e.g. prioritising partnerships or digital marketing), selecting target audiences, creating messaging and designing the customer journey. They can also help other customer-facing team to maximise the relevancy of your proposition and customer experience to your target customers. I use three criteria when determining the ICP for one of our clients: “Likeability” – which customers are going to be worth the most to your business over time, because they spend the most and/or stay the longest? “Available targets” – this is the number of potential customers of any type that are available for your to target, which should be an output of a market & customer segmentation exercise. If possible, I like to think about this as the number of prospective customers who are likely to be ‘in-market’ at any given time, say within a year. “Likelihood” – which prospective customers are most likely to convert, based on how well your product/service meets their needs, or in other words – solves their problem(s). 2.       Mystery shop your customer journey Businesses tend to work in vertical silos, whereas the customer journey progresses ‘horizontally’, from marketing to sales to onboarding to account management. When one aspect of the journey is designed or updated; there is no guarantee that it will fit with the whole. It is just plain difficult to really put yourself in your prospect or customer’s shoes without going through the same journey as they do, and mystery shopping is a great way of doing this. Think of this like role play – imagine the situation of a typical customer for your business and try to replicate it. This is the time for some method acting, so be prepared to go full Day-Lewis to best match the real customer experience. Put yourself in the shoes of potential customer per your ICP, and act accordingly. Take notes, screenshots and videos of your experience – for example how long did it take to get a response when you submitted an enquiry. Our research has shown that speed of response to an initial enquiry is closely correlated with customer conversion. To summarise your findings, I’d suggest coming up with some relevant criteria and scoring your experience out of five on each. Create a highlight and lowlights list. Try to specifically call out the points at which you might have walked away. This might be more impactful if you are able to make a comparison to a couple of competitors who you’ve also mystery shopped, in particular if that would be the typical customer journey. 3.       Measure & attribute your Customer Acquisition activities Attribution is the process of determining how different marketing & sales activities contribute to customer acquisition. It plays a critical role in measuring the effectiveness of your efforts and helps businesses to optimise their budgets and strategies for maximum return on investment (ROI) and minimum waste. Ask your marketing & sales leaders to tie each acquired customer to the activities that (i) introduced them to your business and (ii) ensured that they converted. If you get this right, your conversations about marketing and sales should transform from talking about ‘costs’ to talking about ‘profit’. This might cause some discomfort at first, as more commercial scrutiny gets applied to each marketing activity, but this is temporary – a trusted attribution model can streamline decision making and remove tensions between finance and marketing & sales leaders. 4.       Deliver great service to drive advocacy Customer advocacy is most effective, cheapest, and in every case where I’ve measured it, the biggest marketing channel that will never feature in your ROI reports or marketing section of the board pack. I’ve asked the ‘what did you do to start your research’ question many times in primary research in markets as diverse as dentists and cyber security software, and invariably a recommendation from a peer has been cited by about one-third of the respondents. As well as it just being common sense to seek recommendations from informed contacts when you are making a purchase for the first time, there is something deeply social in asking for, and giving a recommendation. A great recommendation builds relationship capital – and a poor one can damage it. Now, pause for a moment and think about how much money your marketing team spends driving customer advocacy, versus say, running paid search ads or paying a team outbound SDRs to cold call prospects. The imbalance is often striking. You can start to address this by measuring customer likelihood to recommend with Net Promoter Score and addressing the pain points that prevent existing customers from advocating for your business. As an investor or CEO, your ability to work through these six steps will depend on the calibre of your marketing and sales leaders. One of the questions I’ve found to be most helpful in determining this is to ask: ‘where would you spend your next £1?’ Of course, this could be £100, £10,000 or £1 million depending on the size of your marketing budget today – but this question helps you and them to understand both the strategy they’re pursuing and their understanding of what is working /not working amongst their activities today. The most important thing to say about this question is that there is no single right answer. The silver bullet is not TikTok ads, billboards on the tube, attending more trade shows or a shiny new marketing automation platform. In fact, it’s not really about the ‘what’ of the answer at all, but the ‘how’- the thought process that has been used to answer your question. Ideally, a thought process that has happened long before you’ve asked the question. Think back to your exams at school – we are more interested in seeing the workings than the final answer. If you are developing a value creation plan in the Business Services sector, you will likely have many levers available to drive growth, but almost certainly one of the highest potential opportunities will be adopting a more strategic and commercial approach to customer acquisition. The four steps I’ve highlighted will support you in identifying the biggest opportunities and create a ‘north star’ for your marketing and sales leaders to follow. If you’d like to discuss how you can acclerate customer acquisition, please Contact Us.

“Google Chrome to block third-party cookies by the end of 2024” – you may have read this headline or one like it, seen it in an article covering any of the major digital advertising platforms like Google or Meta, or even heard it in a board meeting. It sounds like it’s important, but you don’t really know what it means. Does this require “putting too much milk in your tea” or “the house is on fire” level of worrying? You therefore either assume other people will know more about this subject than you and don’t ask, or when you do ask, you find it hard to judge whether you are getting a reasonable answer. If this sounds familiar, then you’re in the right place. We'll set out the basics of how web tracking works, the impact of the various privacy-driven changes over the past few years, and the upcoming changes in Google Chrome. We’re not technical tracking experts, but almost all our work involves using the outputs from tracking, and when you are running an ecommerce business you certainly feel motivated to understand how it works – as without it you are effectively ‘flying blind’. But if you are a senior marketing leader, CEO or private equity investor – we’ll help you to understand what you should be worrying about and what questions you should be asking. How does web tracking work? For our purposes, in this article we’re going to focus on a subset of web tracking capabilities relating to understanding the behaviour of users on your own website – which sources they arrive from, what they do and what they buy. This is key to accurate attribution and measuring marketing ROI, important factors for any investor-backed business seeking above-market growth. We need to understand the two key components of web tracking: 1.       URL parameters: if you see a '?' in the address bar of a webpage, everything following it relates to web tracking. There is a standard structure used, called UTM parameters, which track certain dimensions like the source you arrived from or which ad creative you clicked on – these are appended to the links that you would have clicked on to arrive on the website. You can test this by deleting all the tracking parameters in the URL and re-loading the website. 2.       Cookies: these are small text files that record information in your web browser relating to your activity on a website. For example: a unique anonymous identifier; which pages you visit; and if you add any products to your basket or make a purchase. These cookies can either be ‘first-party’ - meaning they can only be accessed by the website you are visiting, or ‘third-party’ - meaning they can be accessed by any website using the third-party provider’s code. When you see adverts ‘following you around the internet’, these are relying on third-party cookies – so it’s not hard to see why these have been the subject of privacy concerns. You can see which cookies have been placed by a website when in Google Chrome by pressing the F12 key, navigating to the ‘Applications’ tab and selecting ‘Cookies’ from the left-hand menu. Cookies are placed at a browser level, so you if you visit a website from difference browsers or different devices, you’ll receive additional cookies. Google Analytics cookies normally last for two years, but this can be configured. When you look at the performance of your website in Google Analytics (the web tracking tool used by >85% of the world’s websites), almost all of the data has been gathered by some combination of URL parameters and cookies being created and logged. Web tracking is something that requires constant management - whenever you change your website, upload new content or make changes to your digital marketing activity, there is a risk that tracking could be corrupted or missed altogether. It is important to have a robust approach to monitoring tracking as it is not normally possible to retrospectively backfill any missing data. What has been changing with web tracking? General Data Protection Regulation - GDPR (2018) Arguably one of the most important changes to online privacy was the introduction of the General Data Protection Regulation (GDPR). It harmonised data privacy laws across Europe and introduced the requirement for explicit and informed consent from users to store cookies, where before consent was assumed through the ‘privacy policy’ (you’ve read that, right?). Website owners are now required to have explicit consent for each type of cookie (often presented as ‘necessary’ and ‘optional’). Safari Intelligent Tracking Prevention (ITP) (2018) Shortly after GDPR was introduced, Apple’s Safari became the first mainstream browser to block third-party cookies by default and apply lifespans to first-party cookies. As the second most popular browser, this affected 20% of total search traffic, significantly impacting businesses that rely on third-party cookies to target their advertising like Meta. Google Analytics 4 (2020) Google Analytics 4 (GA4) was released as an update to their Universal Analytics (UA) platform to move away from third-party cookies and prevent the collection of personal information post-GDPR. For example, there an explicit section in its Terms & Conditions confirming that a website may not store any personally identifiable information such as IP addess within GA4. For most regular GA users who we work with, the switch to GA4 was painful, with a significant reduction in the platform’s ability to run reports and understand website performance. However, the data structures that can be accessed via the API or in the Google BigQuery data warehouse were an improvement, and the shift to use first-party cookies means that GA4 will survive the current trend of browsers blocking third-party cookies by default. GA4 also added improved consent management features supporting opt-out options for website visitors (known as ‘Consent Mode V1’). GA4 Consent Mode V2 (2023) Consent Mode V2 aims to ‘improve user privacy and data compliance’ with mandatory enforcement for all companies using Google Analytics or Google Ads (PPC) in March 2024. In V1, users who did not explicitly consent to cookies would still have their event data tracked and sent to Google ‘anonymously’, to train their machine learning models. In V2, alongside some other compliance updates, Google have provided website owners with two options, “basic” and “advanced”. Basic mode means that the website visitor must respond to the cookie consent banner before GA4 loads. In advanced mode, GA4 loads when the website loads, but users who do not respond to the cookie consent banner will still be tracked via ‘Cookie-less pings’, and their data will still be used to train Google’s ML models, to estimate the behaviour of users who declined first-party cookies. Google Chrome Third-Party Cookie Blocking (2024) Google Chrome will block third-party cookies in H2 2024 and is already rolling out its ‘Tracking Protection’ feature to some users on a trial basis. With a market share of 65% of web browser usage, this will have a significant impact on any business reliant on third-party cookies for web tracking. What does this mean for you and what should you do? The combination of the changes to web tracking since 2018 means that even with the privacy-protecting changes in GA4, not every website visitor is tracked. Based on a sample of four of our largest ecommerce clients where we can compare transactional data with Google Analytics, consistently 75-80% of online conversions can be tied to individual, anonymous website behaviour tracked in GA4. So, whilst we’ve lost some visibility, we aren’t yet flying blind. When assessing marketing performance, we tend to allocate those un-tracked conversions pro-rata with those that we can track. Google’s Consent Mode v2 may try to do something a bit more scientific but for most businesses, this isn’t necessary. The upcoming changes in Google Chrome are unlikely to adversely change this core tracking ability, as they impact third-party cookies rather than first-party cookies as used by GA4 – so in that sense, you don’t need to worry. If you’ve relied on social media channels for paid advertising or run retargeting activity (serving display ads to your recent website visitors after their visit), you will have seen a more significant impact from changes relating to third-party cookies, most notably Apple’s ITP. This would have made it harder to track and target your specific customers and their ‘lookalikes’, reducing advertising effectiveness and increasing cost. Platforms such as Meta have changed their tracking methodology to mitigate some of these issues, but Chrome’s upcoming changes will likely impact this further. If this applies to you, I think this is a great opportunity to really test the efficacy of these types of advertising through incrementality testing (for example, only running the activity in one geographic region to allow for comparative analysis). It also forces you back to more ‘analogue’ contextual targeting techniques – instead of ‘following people around the internet’ at an individual level, you can understand your audience as a whole and think about which other types of websites they might visit. This should also serve as a catalyst to ensure you are collecting identifiable data from your website visitors – subscribing them to your mailing list or offering demos and downloads which require contact information. This type of legitimately acquired data is always going to be more reliable for targeted advertising than anonymous third-party cookies. What questions should I ask? If you are attending a management or board meeting and want to understand the current state-of-play for a business’s web tracking, you could ask: (1)    Do we have web tracking expertise in house via a trusted partner? This is a mission critical area if your business drives meaningful demand or conversions online, and it would be a risk to not have access to skilled resources at short notice. (2)    How many of our online purchases or conversions can we tie back to identifiable, anonymous website visitors (i.e. how often is GA4 able to track website visitors at an individual level?) (3)    How reliant is your marketing activity on retargeting and/or paid social activity? If this drives a meaningful proportion of your revenue, are you using contextual/aggregated targeting rather than relying on third-party cookies? It may also be worth asking how the business was impacted by ITP in 2018. We’ve covered the basics of web tracking, the recent changes, and how upcoming adjustments in Google Chrome might affect your business. You don’t need to know every detail of technical web tracking to ensure your business is taking the correct steps - I’ll save describing cross-device joining and server-side tracking for another day! There is no need for panic - we work with this type of data every day and still have plenty of ways to understand and improve website performance with Google Analytics and internal data after the privacy-driven changes of recent years. But it is also important to not be complacent. There will no doubt be further changes in the future so making sure you have access to sufficient technical talent is key. If you’d like to discuss how you can understand the role of web tracking in measuring marketing effectiveness for your business, please Contact Us.

CEOs and PE firms alike have mastered the art of value creation through improving financial, talent, and operational efficiencies, but sometimes go-to-market market performance improvements seem to cause more trouble, and nowhere is this more prevalent than in pricing. Though we’ve covered pricing in a previous article, it can feel very theoretical, so I wanted to hear from someone who’s been on the front lines for some more practical advice, and who better to provide that than a seasoned pricing leader like Chris Pople, Head of Pricing at Antalis, and previously of Adecco, SIG, Cromwell and RS Components. Chris has been working in pricing for 15 years, and with that brings a wealth of experience on the science, and art, of pricing. I wanted to get an idea of the do’s and don’ts of pricing; the quick-wins, common pitfalls, and best practices that Chris has picked up on throughout his career, and as he was introducing his work, I learned my first lesson. “It’s not just about the numbers”, he begins. “In most of my pricing roles, I spend less than 10% of my time on pricing. Most of it is focused on change management, and getting businesses focused on value based-selling.” He emphasises that most businesses lose focus on what they do to solve the customer’s problem, and according to Chris, realigning the whole organisation to those values is an important early step in any pricing strategy. Drawing from his experience with growth consultancies, and his love for Leicester City FC, Pople offers a new perspective through a football analogy: “Most consultancies see the pricing team as the manager or coach of the team. I see us more as the grounds staff. We’re here to make the pitch as best as it can be, setting the boundaries on which the sales team play their game.” As our conversation delves into the complexities of pricing strategies, it becomes clear that Pople advocates for a more holistic approach. “Pricing,” he asserts, “Is one of 5 or 6 functions that bring value to the customer. Very rarely have I seen a pricing project executed by a pricing team on its own.” He lists the teams he most often collaborates on these projects with: “Essentially the whole business entity”. He says, describing how these functions work together to generate value, articulate it to customers, and represent that value with a price, then concludes:  “I would say a more accurate representation of pricing is as a part the customer value management portfolio of functions.” As he sits back, I take a moment to dig deeper on the teams involved, inquiring about the lack of pricing teams in most organisations, and to whom the burden usually falls. “The clever organisations are creating their own pricing functions,” He replies, “but in the vast majority of cases, pricing has been a growing function from within, not standalone.” He talks about pricing being integrated into sales, finance, product development, and the various associated drawbacks, then argues that the best place for pricing is within a transformation team. “All companies are on a transformation journey, just at different stages.” He then addresses some typical points of resistance to such changes, often hearing ‘we haven’t got a pricing problem’ or ‘that’s the best we can do in the market’, and the plight of the sales team, who typically receive mixed messages about the strategy of the organisation. Then Pople shares a trick he commonly employs to rectify this: “I like to get them into a conversation: what are we famous for, what are we known for, what do we also do”. By segmenting the product range or service offering in this way, he can start focus pricing competitiveness in the ‘famous for’ areas, whilst margin enhancing at the other end of the spectrum, simultaneously helping the sales team to understand the organisation’s core values. During his tenure as a pricing specialist, Chris often meets resistance to some of the changes he suggests. To mitigate this, he likes to find a set of advocates in the sales community: “I’ll take someone through the pricing logic, get them bought in, launch it, and when they start seeing results those advocates are all in. Then you’ll get others who see what’s happening and say ‘well I can do that, can you help me?’, and slowly you’ll bring people around.” He adds “You’ll always get some people that are never going to buy in, so I take the 80-20 rule. If I can take 80% of the people on the journey with me that’s good enough, I’ll let the management team deal with the other 20%.” Reflecting on mistakes and lessons learned, he stresses the importance of incremental change. “The biggest mistake,” he shares, “is trying to do things quickly for impact when actually the business really isn’t ready for it.” As we approach the end of our allotted time, both with less interesting meetings looming, I take the opportunity to enquire about some of both the surprisingly simple, and deceptively complex, changes that he’s implemented in the past. “Some of the easiest things to do are reviewing terms, whether its discounts, contracts, etcetera; Harmonising price distribution, and categorising your potential tactics by risk so you know where to start.” One of the hardest things to get right, he explains, is truly understanding competitive pricing. Due to a lack of price transparency in the market, people often get uncomfortable extrapolating what limited data they have to make more informed decisions. He recites the common steps he takes: doing a contractual terms review, clearing out loss making products/clients, looking at sales behaviour, challenging them, and setting a strategic direction, then finishes with one final analogy: “Often pricing seems like a chasm that you’re trying to leap, but you don’ have to cross in a standing jump, you can build momentum with a series of small changes and by the end, you might not even realise you’re on the other side.” Chris’s Tople Tips: Focus on value-based selling Get the whole business involved “What are we famous for, what are we known for, what do we also do” Find your advocates in the sales function (80/20) Start at low risk changes, build momentum Make small, incremental steps If you’d like to discuss how you can understand the drivers of customer value to inform pricing strategy for your business, please Contact Us.

Making customer-focused decisions vital to value creation can be an intimidating task when you feel blind to what is going on within your business. In my time at Coppett Hill, I’ve become used to hearing the most common concerns of Chief Executives, Chief Marketing Officers and Private Equity value creation leads. Frequent questions include the measurement of customer lifetime value, which prospective customers to prioritise, and how to improve the customer journey to increase conversion. From the experience of my colleagues, I’ve learned that the most common (and arguably most distressing) answer to these questions in a boardroom is ‘we don’t have the data’. If you happen to be in one of those roles I’ve mentioned above and a question has made its way on to your desk, there is a good chance it is of high strategic importance – which may well require some of the missing data mentioned above. Why do we ‘not have the data’? First of all, it is rarely the case that the data you need is not collected at all – almost all aspects of your customer journey, product and transactional relationship with customers and suppliers is digitised in some way. Even if you are after customer feedback or competitor intelligence you can gather with periodic qualitative research or mystery shopping. Should we clear the first hurdle and have a potential source for our required data, we might be faced with data which we not have confidence in, or even more perplexingly, several different data sources offering contradictory estimates of the same metrics. Sometimes the problem can be as simple as different systems holding data for different geographies, or different products/service offerings. This confusion can be compounded by a lack of analytical skills within the organisation to delve deeper into the data and search for a rational explanation for these differences. The question is, when you have several data sources all claiming to be a ‘single source of truth’, which do you choose to place your confidence in? In particular, when each might have its own group of loyal users within the business using it on a daily basis? From my experience, often the answer has been none of them. We often start our work with clients by building a bespoke ‘customer data platform’ that is a foundation for insights, recommendations and informed decision making. How can I build a customer data platform I can trust? 1)      Decide what is important. The first step in this process is to find relevant input data sources that we are going to combine into a centralised database. The input data sources differ from business to business; however, we would generally expect there to be some versions of ecommerce/sales software (perhaps even transactional data from a finance system), marketing tools such as Google Analytics, marketing automation/email software and customer experience software in most growing businesses. You might also include product usage data (if you sell a software product) or timesheet data (if you sell professional services). You will want to also compile more ‘fixed’ data or assumptions relevant to your business – think financial inputs like cost of goods sold (COGS), direct staff costs, payment processing costs or perhaps financial forecasts. Any input data source that you think could conceivably contain some data relevant to metrics you would like to generate, should be included. It’s okay if some things are assumptions where accessing actual data is not justified by the risk-reward, for example allocating payment processing costs at a transactional level. 2)      What do customer interactions with your business look like? It helps at this point to consider all the different interactions it is possible for a customer to have with your business. Mapping each of your data sources into a series of ‘events’ in the customer journey, such as an enquiry, purchase, or customer success contact allows for more powerful analysis of your customer data platform. It helps to expand the scope of questions it is possible to answer to include customer-centric issues like conversion and retention, as well as segmenting top level metrics like customer lifetime value (LTV) by real-life behaviours, such as whether a customer has interacted with your customer success team (more on this later). 3)      Putting it all together. We can then start the process of joining these data sources together. You will typically need to use an ETL tool (Extract-Transform-Load – such as Fivetran or Daton) to extract the data from your source systems, and a data warehouse to store it (we use Google BigQuery, as we have found it to be fast and cost effective to maintain). Once you have all your data sources successfully imported into your data warehouse, you can start the task of cleaning and structuring your data. The goal is to end up with a comprehensive dataset of customer interactions you are interested in, allowing you to understand the complete journey of a customer from the point they first interacted with your business, to the present day (and to set up key metrics on top of that). To keep this data up to date, you will need to utilise the scheduling capabilities of your data warehouse – using BigQuery, you can configure the queries which underpin your dataset to run as frequently as every 15 minutes. 4)      Getting the insights. This where you see the benefits of your hard work! You can connect a powerful visualisation tool such as Tableau to your data platform, and start to answer your strategic questions. It’s one of the most satisfying parts of my role when I can share an insight with a client that they have never seen before. If your data is updating routinely, you can also build KPI dashboard to allow you to monitor leading indicators of success. Why can creating a single view of customer behaviour be difficult? Locating the data for event types you are interested in isn’t always straightforward. Untangling the data structures in the backend of your existing software tools to get a view of event type, details and customer attributes can prove a challenging task, as visually demonstrated by the anxiety-inducing web we extracted from a Coppett Hill client’s Salesforce system. Accommodating for this involves a lot of careful inspection, common sense checking, and often quite complex logic to evaluate for nuances between source data. Something which may at first seem like a dead certainty to appear in a straightforward, easy to understand fashion within a data export, given its significance, may in fact be much harder to find. There can often be some digging involved to discover what corresponds in the backend to the metrics that you and your team use every day in the web interface. Labelling can also be an issue – when you have 50 different date columns within one table, figuring out which of these to use isn’t straightforward. Amalgamating data from various sources also relies upon the existence of a ‘common key’. To explain (without getting too deep into the weeds), if you would like to combine data from multiple sources on the same event, you need a column which is present in both data sources to ‘match’ on, for example a unique Customer ID. This may sound simple enough, but when these columns are formatted even slightly differently, you run the risk of losing heaps of valuable data – which of course has trickle-down effects. Metrics drawn from the top layer of a bespoke customer data platform can be wildly thrown off by just one of these rogue ‘matches’. Difficulty can also come when datasets or assumptions change. Establishing how to handle historical data is vitally important – should a financial input change in the future, how do you enact this going forward, but ensure that the accuracy of your historical profit data isn’t compromised? We have found that defining a set of validation tests, as well as piece-by-piece implementation and a constant feedback loop, have been helpful when navigating these issues. We are sometimes asked 'can't we just buy a piece of software to do this for us'. In our experience, the sheer variety of datasources required, their changing nature over time, and the ability to perform wide-ranging analysis leads us to recommend building your own customer data platform - using in best-in-class software components for collating, storing and visualising data. How can I take this to the next level? Each data source typically comes with some data on each individual customer – but not all of it. When you compile the data locked within several sources into one centralised dataset, you begin to get a much clearer picture of who your customers really are. The real value of a bespoke customer data platform comes from when you start to segment customers against a measure of their worth (such as LTV – we would recommend focusing on up to three key measures at first). Example segmentations include: Customer attributes (e.g. where they are based); First purchase characteristics (e.g. initial value or products selected); and In-life behaviours (e.g. if they’ve contacted you), including delving into the results of experimental marketing schemes and much more. Using ‘flags’ when working with our clients’ data can make the segmentation of customers much more straightforward when conducting analysis (an example flag could be whether a customer has received a particular type of communication). Alongside a reliable top-level estimate of the key metrics we described at the start of this article, a customer data platform gives you the opportunity to view these metrics at a segmented level – allowing you to make decisions which reflect key differences between these segments, as we set out in our guide to increasing LTV. For example, if you were to see that your customer buying Product A had a much higher LTV than those buying Product B, you might want to prioritise marketing channels that attract customers interested in Product B. One other way of getting the most from your customer data platform is making the output visualisations/dashboards accessible to the whole team. The need for back and forth with an in-house data science team is eliminated. The whole team can see the whole picture the whole time, effectively removing any potential variance between the board level view, and the operational view of the health of a business. If you’d like to discuss how you can join your customer data sources to understand these relationships for your business, please Contact Us.

Your sales team is telling you one thing, your finance team is reporting another, and your cash position doesn’t quite add up. This scenario is incredibly frustrating and concerning as a business leader. As a Board member, I found this situation to be more common than you’d expect, and it was usually a red flag for underlying issues. Often these were symptoms of underlying weaknesses causing revenue leakage—a common yet often overlooked challenge. Revenue leakage – it sounds like something you probably want to avoid, but what is it exactly? And how should you be thinking about it? In this article we’ll be giving you a rundown of what it is, common causes, how to identify it and some potential solutions. An estimated 42% of companies experience some form of revenue leakage, and for B2B businesses I would guess that that figure is probably closer to 60%+. What is revenue leakage and some of the most common causes? Revenue leakage refers to revenue lost due to inefficiencies, from the initial quote stage through to receipt of payment. Most commonly it refers to revenue that has been earned but not collected due to operational errors and weaknesses in systems. It can also refer to lost potential revenue due to inefficiencies in the sales funnel e.g., lack of systematic follow-ups with hot leads or failure to follow account management processes. Revenue leakage is likely to be a bigger issue in B2B businesses, especially those with multiple products and/or complex sales structures. Revenue leakage can be subtle and often go unnoticed. It’s like a dripping tap, happening in little bits, but with the potential to add up to a significant amount over time. Some common causes of revenue leakage are: Pricing, discounts, and promotions that aren’t centrally managed: e.g., introductory pricing going on for too long, discounts that aren't necessary to get or keep customers (just check how often your sales reps are applying their maximum permissible discounts), extra services being thrown in for free. Contractual pricing not being followed: e.g., not tracking and charging clients’ volume and usage patterns, unenforced penalties, undercharging for billable time as part of services revenue, not applying contractual annual inflationary prices increases. Manual processes, especially manual invoicing, leading to data entry errors, incorrect billing, services being omitted or delays between sales closing and invoicing. Poor data management: e.g., sales spreadsheets not integrated with billing systems, inconsistent data entry, inaccurate customer information. Gaps and inefficiencies in the sales pipeline: e.g., delays in sending quotes out or slow approval processes leading to lower conversion, renewal reminders not being sent out, upsell opportunities being missed. Poor handover between teams: e.g., marketing leads not being followed up with by the sales team, information from sales conversations not being captured and passed on to customer services. Incompatibility between systems – this is often the case in businesses that have undergone M&A or have legacy products alongside a newer business unit e.g., billing systems not linked to original proposals and contractual terms, different billing systems for different parts of the business. Why focus on revenue leakage? Revenue leakage may not sound particularly strategic, but it can be a significant value driver and should be on the Board’s agenda at least once a year. These are four key reasons management teams and investors should be thinking about revenue leakage: It has a direct impact on profit – revenue that hasn’t previously been collected, and suddenly is, tends to fall directly to the bottom line. Research shows that most companies lose 1-5% of EBITDA to leakage annually. It can be a key lever for growth during difficult macro-economic periods. Addressing revenue leakage typically requires operational changes rather than relying on increasing market share or tapping into a growing market. Optimised revenue leakage is usually linked to a ‘well run business’ which can have a positive impact on overall valuation - diagnosing the causes often uncovers inefficiencies in processes and systems, manual interventions, and poor data management. Addressing these should not only increase revenue, but also improve operational efficiency and can lead to other benefits such as better data, improved visibility, and cash flow management. During a sale process these are all ‘green flags’ for a well-run business which can add to the valuation multiple. Improved customer satisfaction. Unnoticed errors which lead to revenue leakage can also lead to frustration for customers (for example dealing with billing errors), make companies seem unreliable and unprofessional, and can damage customer relationships or a company’s reputation. Questions to ask your sales or finance director to identify revenue leakage issues Revenue leakage can be tricky to spot due to the fact it may exist in small pockets and below the level of detail of management reporting. If you want to assess the potential impact of revenue leakage in your business, here are a few suggested areas to ask about: Process – What are the steps in the current sales and billing funnel where is there potential for manual errors, system incompatibility, or missed conversion opportunities? Pricing – Are average prices and year on year changes consistent with the stated pricing strategy? One diagnostic approach is to conduct a review of a selection of customer accounts and compare prices in the system with the amounts that clients actually paid over the past years. Cashflow forecasting, late payments and bad debts – How accurate is cashflow forecasting? Are late payments and bad debts in line with your industry? Are they growing? Is there an understanding of the root causes? These are common signals for poorly managed billing and invoicing. As an investor I’ve been in situations where this started off as what seemed like a small issue but a definite red flag. When management dug into it, it turned out to be the tip of the iceberg and uncovered a whole tangle of legacy billing issues. It is much harder to get customers to pay up if you’ve been sending them erroneous invoices for the past 2 years! Pipeline – How accurate is your pipeline and revenue forecasting? Is there a big discrepancy between initial estimates and final quotes? Conversion – Are there noticeable ‘holes’ in the funnel where conversion is lower e.g., certain teams, products, channels to market? We think most companies would benefit from putting ‘Revenue leakage’ on the board agenda at least once a year. Ask the CFO to do an audit with help from the sales team - this might involve walking through the steps in the current processes and identifying potential areas for errors. They should also form and test hypotheses based on the indicators above e.g., check the largest accounts, accounts with late payments, legacy clients, accounts with the most complicated contractual terms. What are some solutions? Simplify your billing and invoicing, keep it consistent and automated where possible. Try to avoid too many tailored pricing options that create leeway in the sales team. Implement clear approval processes for pricing; regular account reviews, check client profitability regularly e.g., with timesheet or allocated direct cost data. Implementing automated billing systems not only reduces manual errors but also streamlines cash flow management, a crucial aspect of profit maximisation. Centralise processes and automate data capture as far as possible – this will help reduce manual errors and enable real-time monitoring, approvals, and tracking. Proper use of a CRM like Salesforce can be invaluable. Of course, it’s critical to ensure the quality of the data entered. Remember, garbage in – garbage out! With your sales funnel data integrated in a central source of truth, you can use automated reporting or AI to spot discrepancies and opportunities, such as differences between quotes and agreed contracts or salespeople that regularly ‘undersell’ certain add-ons. Conduct regular financial audits, monitor customer accounts, and tighten financial controls to identify discrepancies, errors, or fraud. Improved systems and data capture should provide better visibility and insights into data like cashflows, pipeline and resource utilisation. Train your employees, especially those in sales, customer support and finance, in revenue management processes and contract compliance. If you are asking people to change their behaviour, especially around CRM use, pricing, or enforcing penalties, it is critical to provide them support from the top in implementing this. As you can see, revenue leakage can be a broad umbrella for many issues. Hopefully this post gives you a starting point for assessing your own business and some ideas for where to look. Beyond the P&L impact, we believe that addressing causes of revenue leakage can lead to a more efficient and well-run business which makes it an important value creation lever. If you’d like to discuss whether revenue leakage might be an issue in your business and how to approach it, please Contact Us. All views expressed in this post are the author's own and should not be relied upon for any reason. Clearly.

We’re continuing our series on alternative indicators of growth, looking at whether any ‘vanity’ metrics are correlated with or predictive of profitable growth, based on the work we do with our clients to create a single customer view across their various marketing and sales data sources. Today we are focusing on enquiry response time – how many times have you filled in an enquiry form on a website and felt like you were just shouting into the void? Our conclusion is that this is one of the most impactful levers for conversion rate optimisation in B2B and long sales cycle B2C, that almost always works to accelerate customer acquisition. Why is enquiry response time important? At the start of most considered purchase journeys – perhaps for a first-time purchase, or one where getting it right is particularly important - purchasers are doing some form of research into potential providers & their propositions. For both B2B and B2C purchases, this will typically involve some combination of online searching and seeking recommendations from trusted contacts, then a review of the suggested providers. Think about the last time you looked at booking a holiday, obtaining a mortgage, or buying a new piece of software at work. For those journeys where there isn’t a ‘buy online’ option, purchasers will often then contact a handful of providers (previous research I’ve done suggests between 2 – 5 options). In each business on the receiving end of these enquiries, I’ve seen that conversion rate is highly correlated with the speed of response. If you imagine your own purchase journeys you can rationalise this effect - as consumers we infer that those who respond more slowly are less keen on our business and/or less able to service it (this of course may not be right but is a common heuristic). We were recently able to demonstrate this with a Coppett Hill client, where we saw that conversion rate for enquiries responded to within 3 hours was 3x that for enquiries responded to after 24 hours. This effect was also visible when we looked at the time of day enquiries were received. Our client was receiving enquiries from international locations but operated a sales team with UK hours, and as a result conversion rate dropped materially when the sales team were not online. This insight led to our client introducing much tighter SLAs for the speed of response, adjusting their opening hours, and adjusting the times that they were running paid digital marketing to generate enquiries. We were also able to combine this with some work on their Ideal Client Profile so that they are prioritising responding to the ‘best fit’ enquiries – not all enquiries are created equal. What does this look like from a prospects’ perspective? To Illustrate this, we’ve tested response times from a group of five ISO 27001 certification providers – who sell a mix of software and services to help businesses to achieve this security certification. We chose this group as this is something that Coppett Hill is genuinely considering, but also because the five providers we sampled have Private Equity investment so have had some level of external scrutiny of their sales processes. We made these enquiries at the start of the business day, and captured the complexity of the website enquiry form, whether we received an automated acknowledgement and the time it took to receive a phone call (the promised response in all cases). The fastest provider called us back after 43 minutes, whereas the slowest response took nearly 6 hours to respond, and one didn’t call us at all. This illustrates that even in a mature, competitive category there is still scope for improvement - we could feasibly have already booked 3 demos by the time we heard from the Provider D, and we would never choose Provider E in this example. One caveat is that the responses we received might reflect that we were de-prioritised based on being less of an Ideal Client Profile fit. Interestingly just one of the providers offered the opportunity on their website to immediately book a demo rather than requiring a call back from sales. How should I think about enquiry response time for my business? Producing this type of analysis can be hard – in the above client example we linked website form fills in the marketing automation platform, the timing of outbound calls from the telephony system and prospect conversation status from the client’s CRM. But once you have this, the typical dimensions to look include: The timing of calls – evenings, weekends etc.; The source of enquiries; Any customer attributes, for example whether they are a fit with your Ideal Client Profile; and Response time by salesperson or location. One of the most important things to keep in mind is the Flaw of Averages. You should look at the outliers – your average response time might be 45 minutes, but how many clients wait more than 1 hour, or more than 3 hours for an individual response? You could also think about how automation can offer some protection e.g. mentioning your average response time next to the enquiry form on your website, sending an automated acknowledgement email which sets some expectations (perhaps different versions for whether someone has submitted an enquiry within your office hours or not), or maybe even adding an appointment booking tool to your website. If you have an enquiry response step in your customer journey, I’d recommend testing this and looking at how you can increase response times to increase conversion and accelerate customer acquisition. You could also test this yourself with a mystery shopping exercise. If you’d like to discuss how you can join your marketing data sources to understand these relationships for your business, please Contact Us. All views expressed in this post are the author's own and should not be relied upon for any reason. Clearly.

Many marketing reports I have reviewed over the years have focused on ‘vanity’ metrics like impressions, likes and views - which look impressive on the surface - but made no mention of profit or return on investment (ROI). In the spirit of challenging assumptions, this is the first in a series looking at whether any of these ‘vanity’ metrics are correlated with or predictive of profitable growth, based on the work we do with our clients to create a single customer view across their various marketing data sources. I have always been fascinated with alternative indicators – for example measuring light pollution from space as a proxy for African economic growth or using satellite imagery of car park utilisation to predict retail like for like growth. First up in this series is email open rate. We have looked at this in two contexts: in a long sales cycle business (think B2B enterprise software or high value consumer goods) vs conversion to purchase, and in a transactional B2C business vs lifetime value. Example 1 – long sales cycle conversion This example represents a very high value B2C purchase, with a sales cycle of c. 1 year – so I think of it more like a B2B sales process. We see that there is a linear relationship between marketing email open rate (i.e. excluding 1-1 contact with salespeople) and ultimate conversion. Example 2 – transactional B2C lifetime value In this typical B2C ecommerce example, in a category with a high purchase frequency, the relationship is slightly different – getting email open rate above c.20% correlates with a meaningful increase in customer lifetime value (measured in terms of profit of course). Above this, there is a still a positive relationship but less strong than in our first example. What we have also looked at here is whether there might be covariance with the number of emails received – but when you isolate to just those customers who have received >50 emails, the trend is almost identical. How can we use this insight to drive growth? Of course, you may be wondering- is this just correlation or more fundamental causation? In the first example, common sense says that a prospect who is more engaged is more likely to open emails. In the second example, a customer who feels a connection to a brand and its content may well be more likely to open emails. I would make the case that in some ways this does not really matter, because the most valuable way to use this insight is as a correlation, in other words a predictor of prospect conversion or customer lifetime value. This could allow you to prioritise sales resources, direct churn prevention activities or indeed simply to produce a more accurate forecast of business performance. As to whether working on your email strategy can increase the correlated business metric – that is something you should test. With both client examples described above, the next layer of detail suggests the opportunity to make gains – looking at the specific email campaigns, automated journeys, and scope for more A/B testing. One of the best characteristics of email marketing as a Chief Marketing Office (CMO) is that compared to your website, app, or other digital products, you are likely to have full control of A/B testing without the need for your tech team to get involved. Send days, times, subject lines, and email content can all be optimised. If you have the data available, check this comparison to conversion rate and lifetime value for your business. If you do not have this at your fingertips, it is worth the effort to start to tie your different marketing data sources together to create a single view of the customer journey to uncover insights such as this. Next up in this series will be enquiry response time – please do suggest any other indicators you would like to see tested. If you’d like to discuss how you can join together your marketing data sources to understand these relationships for your business, please Contact Us. All views expressed in this post are the author's own and should not be relied upon for any reason. Clearly.

Around two thirds of trackable web traffic comes from search engines, whether from paid listings (paid search or PPC) or organic/free listings (organic search or search engine optimisation - SEO). The chances are that search represents a very meaningful source of online traffic, leads and customers for your business – even if it is at the start of a long B2B purchase journey. It follows that when you are setting your digital marketing strategy, you should be seeking to understand your potential opportunities for growth within paid and organic search, and then tracking changes on an ongoing basis. Search engines helpfully provide a lot of information of advertisers on the performance of their paid search activities, but this is not the case in organic search meaning that marketers must rely on third party tools to track their SEO rankings. In our experience, organic search is overlooked in terms of its commercial importance to most organisations, receiving much less Management time, fewer metrics in the board pack and insufficient investment than other marketing channels. Your SEO rankings can often account for 50% of new customer acquisition once you have clear picture of marketing attribution, at a very attractive Cost Per Acquisition CPA compared to other channels. This lack of attention results from a combination of the difficulty of measuring/tracking the value of your SEO rankings and the (misplaced) idea that organic search traffic is both hard to influence and in terminal decline, so why spend time focusing on it. A Search Headroom analysis that is based on your SEO rankings can help change some of these perceptions and help to bridge the gap between senior managers and technical SEO practitioners. What is a Search Headroom analysis? A search headroom analysis highlights a business’s share of its potentially addressable organic search traffic at a specific point in time. The higher up your business appears in the organic search rankings for any given keyword, the greater your share of traffic will be. You can think of this like a digital version of a traditional ‘market share’ analysis. The difference is that traditional market share is based on the ‘stock’ of customers in a market (e.g. a car manufacturer’s share of all the cars on the road today), where as a search headroom analysis considers the ‘flow’, the customers who are actively searching for a given product or service (e.g. a car manufacturers share of the new cars sold this year). Businesses that are growing will often have a higher share of search traffic than their overall market share – hence this can be a valuable leading indicator of growth. In principle there are a handful of steps to follow when creating a Search Headroom analysis: Build a list of your own web domains and those of your competitors; Use a third-party tool to produce a list of all the keywords where each domain appears in the search results, and their respective SEO rankings; Aggregate the results together and remove duplicated keywords, irrelevant keywords, and those where the ranking is so far down the results, they are unlikely to generate any traffic; Combine with data on the overall monthly searches for each keyword; Translate the rankings into estimated traffic for each domain on each keyword (considering both the ranking and other search results page (SERP) features which could impact click-through rate (CTR)); Group the keywords into common sense segments for your product/service; Explore the results at a segment, keyword and even landing page level; and Review the search results for your most important keywords to check for any additional competitor domains to include the next time you update the analysis. Figure 1 - example summary from a Search Headroom analysis showing 'market share' by domain and keyword segment. A Search Headroom analysis is a very powerful tool as it can be built both ‘outside in’ using 3rd party providers of search results tracking, as well as being enhanced with more accurate internal data, for example when estimated CTRs. We have used this approach both as operators and investors as a result, to understand a market overall, dig into competitor strategy or track who is gaining/losing share. You can also apply this methodology in other channels e.g., Amazon. A Search Headroom analysis is also very useful when you are planning big changes in your digital marketing strategy – launching a new website, re-platforming an existing website, or planning a domain consolidation. All these changes can cause significant and immediate change in your SEO ranking that you need to carefully monitor and mitigate. What digital marketing insights can a Search Headroom analysis generate? Understanding your business’s search headroom can yield many interesting insights about your business, your competitors, and your market. For example: Your ‘market share’ of organic search traffic, and how this varies by segment and keyword Trends in your ‘market share’ over time Level of fragmentation/concentration of traffic in your market Seeing where your competitors are winning traffic, but you are not Growth YoY in terms of search volume (10 years ago it seemed like every keyword was going in volume terms, but overall search volumes are now relatively stable, so growth in searches tends to correlate with overall market growth)) The level of volatility in your market i.e., how often SEO ranking changes How commercial/sophisticated the digital marketing strategies are in your market i.e., understanding the mix of organic vs paid traffic (search ads and shipping ads in some categories) Where you are doing well in organic search but not paid search and vice versa, by comparing the Search Headroom analysis to your paid search data How overlapped your market is with other markets that may have similar search terms – think about a market like cyber security where you will find many different overlapping niches as well as job seekers and students searching very similar keywords Seeing your SEO rankings at keyword level (where do you rank vs. where you ‘should’ rank based on the product/service offering of your business) Where you may have recently lost high volume SEO rankings Whether your SEO/ content team are spending time in the right areas to both protect your most valuable SEO rankings and grow your visibility in the areas of biggest opportunity Comparing the performance of your different landing pages (and those of your competitors) Figure 2- example keyword level market share from a Search Headroom. What makes this difficult? Whilst the benefits of a Search Headroom analysis are hopefully clear, this is something that many businesses have never attempted. One of the challenges in the complex, technical nature of search marketing, and in particular SEO. In our experience, many talented, technical SEO professionals don’t think about top-down opportunity enough and for most management teams SEO is the ultimate ‘black box’ where cause and effect are very hard to understand. The closest teams often get to quantitative reporting of their search marketing is a page in the board pack listing their top 10 keyword rankings. There are a few other factors that make producing a Search Headroom analysis hard: The (very) long tail matters – previously businesses I’ve worked with have generated as much as 90% of their organic search conversions from keywords with fewer than 100 monthly searches. You will likely need a dataset with thousands or tens of thousands of keywords, potentially more if you are an established business in a large market e.g., online travel. This means that completing the Search Headroom analysis need more advanced analytical skills which your team may not have. Most SEO tools – and there are lots – track a selection of SERPS and produce various metrics like ranking, perhaps even estimated traffic, but this is rarely out in the context of overall category and certainly doesn’t highlight opportunities and risks – so you need to do your own analysis to produce an overall view of your ‘market share’ as well as being able to drill down. To get a complete view of your SEO rankings you may need to combine data from multiple tools. There are many features that can appear on the search results page and influence the click-through rate for any given ranking. The number of paid search ads, shopping ads, maps, and featured answers all play a role – you ended to look carefully at your own data to make sensible estimates for each potential scenario, again adding to the analytical complexity. The recent emergence of generative AI is going to lead to a lot of change in the SERPs over the next couple of years which will only add to this complexity. Deciding how to segment your keywords can be subjective and requires some test & error – how many groupings to create and how to define them. In our experience, we find it helps to remember that not all traffic is equal in terms of its likelihood of converting, so we will create segments that differentiate by level of intent e.g., whether a search includes a high purchase intent word like ‘buy’, ‘compare’ or ‘reviews’. We will also always create a segment for branded terms as these behave very differently with very high click-through rates on your own brand terms. The changing search engine landscape – this will vary by business and geography, but Google has c.85% share globally, and Bing has been gaining share and has reached 8%. For now, if you build your Search Headroom analysis based on Google you will get an accurate enough answer, unless you are focused on one of the handful of markets where Google is not the outright market leader (e.g. China, South Korea). Novel products / services with limited directly relevant search traffic - I’ve worked with businesses at the vanguard of a new category where consumers are not yet searching explicitly for their product or service in high volumes. This means a Search Headroom analysis will typically show the business as having a very low share of some large, adjacent keyword categories – which isn’t especially actionable in the short term. In these cases, we narrow down the keyword focus to the handful of directly relevant keywords but monitor closely for new keywords which will be likely to appear every month. How can I create my own Search Headroom analysis? None of these difficulties should prevent you from undertaking a Search Headroom analysis – the insights you can generate will be truly insightful, helping you to both spot opportunities and manage risks. At Coppett Hill, we've created our own tool to create Search Headroom analyses for our clients, "Searchscope". We've combined our experience of SEO across many different industries and geographies with proprietary AI to rapidly produce actionable insights that can be updated every month. This saves our clients considerable time and effort in understanding this critical area on an ongoing basis. If you’d like to discuss how you can use your SEO rankings to use our Searchscope tool to create a Search Headroom analysis for your business, please Contact Us. All views expressed in this post are the author's own and should not be relied upon for any reason. Clearly.

Among the many ‘data gathering’ approaches that I learned as a strategy consultant, I always found mystery shopping to be one of the most powerful ways of both understanding the proposition of a business and highlighting an issue with a customer journey or competitive challenge. Ask yourself – when was the last time you mystery shopped your own business, or one you are invested in? If I look at the photo library on my phone from my time at CarTrawler, it is full of screenshots of the Google search results, our booking funnel and emails. Some of my best moments as a strategy consultant were from mystery shopping exercises, including: Countless golf buggy rides around caravan holiday parks in 2009-2010 were a key part of understanding how the propositions of different operators compared – claiming to be interested in purchasing a caravan for my retired mother; Getting thrown out of Chiswick Sainsburys in my first year at PwC for taking photos of the merchandising of the nappy aisle; Visiting 15 pubs in the Channel Islands in one day (which turned out to be a Champions League day making the last few visits particularly tricky); Getting questioned by security at a garden centre – admittedly I can appreciate that it was a bit weird that three 20-something men were walking round taking pictures on a weekday afternoon; and Spending two weeks visiting men’s formalwear shops in Lagos, Nigeria while working with a British brand. Figure 1 - some of my many mystery shopping experiences as a consultant Why is mystery shopping so effective? Businesses tend to work in vertical silos across the journey, whereas customers move through ‘horizontally’. When one aspect of the journey is designed or updated; there is no guarantee that it will fit with the whole. Some teams responsible for part of the customer journey may be incredibly customer-aware, others may be more concerned about improving their own team’s operational efficiency. It is just plain difficult to really put yourself in your prospect or customer’s shoes without going through the same journey as they do. Mystery shopping is a great way of doing this. I’ve worked with a law firm who prided themselves on incredible client service, but were seeing disappointing Net Promoter scores (NPS) . When they dug into the feedback, they found that their accounts team were issuing often incorrect invoices and following up aggressively with clients, eroding the goodwill that the firm has built. This part of the customer journey was effectively ‘hidden’ from the lawyers and senior management. How to mystery shop your own business Think of this like role play – imagine the situation of a typical customer for your business and try to replicate it. This is the time for some method acting, so be prepared to go full Day-Lewis to best match the real customer experience. When they might decide to start looking for the product/service you offer, and how might they try to find a provider like you? Are they searching online, talking to a trusted advisor, looking at reviews or asking their network? You could even get as specific as when in the day/week they are doing it, and on which device, and from where. Then consider what a customer’s needs and expectations are. Do they want a fast, low friction purchase journey? Or will most of them need advice and the opportunity to ask questions? Is this a purchase that they will be making at a time of personal/corporate distress, or as an indulgence? Will they be comparing you against a handful of close competitors or only be considering your product/service? Once you are ‘in character’ you can start the mystery shopping process. You might want to have a pseudonym and non-identifiable email address ready, if your colleagues would recognise your name on a list of prospects! Or you could ask a family member or close friend to do it for you – their feedback may be brutal but it isn’t tempered by having been told by your CTO just how hard it would be to change those landing pages or create an online demo. The exact nature of your mystery shop will vary based on the product/service offered by your business – you might be sat behind your desk, out on the high street or on the phone (or all the above). There are a few items on my standard mystery shopping checklist which might help you: At each stage, capture what you experienced, whether this met your expectations, and how you felt. Take notes, photos, screenshots, make a few videos, and time things (e.g. how long to respond to your enquiry) How well does your messaging (across all touchpoints) describe what a customer is looking for or the problem they have? How clear and compelling are the calls to action – did you feel like it was obvious what you should do next? Go through any online process that your business operates – e.g. a full purchase journey, content downloads, or 'contact us' form submissions. Where are the points of friction? How many steps do you have to go through? What jars with you, for example input validation warnings before you’ve even started typing! At what point(s) did you want to give up? If in your typical customer journey, they might go and look for online reviews or discount codes – make sure to do that as well. Try each mode of contact – contact form, webchat, phone numbers, messaging. Assess the speed of response and the nature of it. Ask a realistic but detailed question and see what kind of response you get. Ask for a demo or call with keenness – and see how quickly it is set up. Could you hypothetically have been speaking to a competitor in that time? If your journey involves engaging with a salesperson and it is possible for you to do this – what did you make of their materials, clarity of communication, understanding of your needs as an (imaginary) customer, and how is price communicated? What supporting comms do you get e.g. emails, content being shared. This is one of those times when you should always subscribe to the mailing list. If your business sells B2B, you could try and present as a poorly fitting customer (e.g. too big or too small) – do your sales team say no? What to do with your mystery shopping findings To summarise your findings, I’d suggest coming up with some relevant criteria and scoring your experience out of five on each. Create a highlight and lowlights list. Try to specifically call out the points at which you might have walked away. This might be more impactful if you are able to make a comparison to a couple of competitors who you’ve also mystery shopped, in particular if that would be the typical customer journey. Then to share with your team, consider the feedback you have for your teams on both (a) having the right process/journey and (b) following the process that’s in place. Understand that aspects of your experience might be exceptional/unusual so don’t instantly extrapolate - mystery shopping isn't the only valid way of understanding the effectiveness of the customer journey and will always be somewhat subjective. But ask the question of how common such an experience might be and seek data to support this. If you are a senior leader, be wary of how your view may be treated. Your team will no doubt know many (but probably not all) of the issues & opportunities that you identify, so communicate your findings accordingly. You also don’t want them to place too much weight on your input vs other research & data gathering activities - don’t be a HiPPO (the Highest Paid Person’s Opinion). And a last piece of advice – don’t use your real address or phone number. My mum still receives brochures from those caravan parks 15 years on and has never forgiven me! If you’d like to discuss how you can better understand and improve your customer journey, please Contact Us. All views expressed in this post are the author's own and should not be relied upon for any reason. Clearly.

The question of “how much to spend on marketing” is one that every business should ask itself. The answer is often “what we spent last year plus a bit more”. Imagine that instead of simply making tweaks from last year’s budget, you had a blank sheet of paper to design a set of activities and costs with the goal of maximising profit growth over a 3-5 year time horizon – a form of ‘zero-based budgeting’. When I took on responsibility for the consumer brands at CarTrawler, I had to answer this question so that I could build a strategy and budget at a time where my knowledge of each marketing channel was fairly limited, so I approached it from economic ‘first principles’. A recent conversation with a value creation leader at a mid-market private equity fund prompted me to try to set out my thinking and share it. In trying to answer the question of “how much to spend on marketing” through an economic lens, what we are really talking about is treating the process of acquiring customers as a demand & supply problem. In this problem, ‘supply’ means the number of customers that we can acquire at any given average Cost Per Acquisition (CPA) and ‘demand’ means the average CPA that a business is willing to pay for a given number of customers to meet its goal for profitable growth. I’m going to describe each of these components in turn, talking through the theory then coming back to the practical application of this way of thinking. The ‘supply’ of new customers & problem of diminishing returns A very common issue in business plans that I see when a business is seeking private equity investment is forecast year-on-year growth in the number of new customers alongside a reduction in CPA. There may be one-off factors that may explain this, but on the whole, if you want to acquire more customers you should expect your CPA to increase. The reason for this is simple – to add more customers you will have to start additional marketing activities which are likely to be less efficient and/or more costly than your existing activities (assuming some level of optimisation has happened over time to lead you to these existing activities). A good parallel to this is the oil cost curve – which plots different sources of oil against their ‘breakeven price’, i.e. the $ per barrel at which it makes sense to ‘activate’ these supply sources. When oil is >$100 per barrel almost all supply sources become economically viable, whilst when <$50 per barrel a range of sources become too costly to extract for the return you will achieve. Figure 1 - Oil Cost Curve, Goldman Sachs Research, “Top Projects 2022”, April 19, 2022) In marketing terms you could think about this as starting with word of mouth as your ‘cheapest’ source of new customers on the left side of the curve, moving through organic search, partnerships, through to paid search, then paid social and perhaps with sports sponsorship as the most ‘expensive’ on the right hand side. I would recommend thinking about what this supply curve looks like for your business – being sure to factor in the full cost per acquisition, including things such as agency & technology costs as well as personnel costs & sales commissions. It can help you to understand whether you are really maximising the potential of your most effective marketing channels before moving ‘up the supply curve’ to more expensive activities. For example – almost every marketing team is leaving ‘money on the table’ with a limited focus on customer advocacy. Of course in real life, the confidence you could have in such a curve would rely on the level of marketing attribution you had in place to allocate new customers fairly between the marketing channels that originated them. It would also be hard to account for new marketing activity where you don’t yet have the data to really understand the true cost per acquisition. It is important to note that we are thinking here in terms of average cost per acquisition. Such an average will almost certainly include some areas of marketing activity which have a very high, uneconomic cost per acquisition that you could focus on to find efficiencies - a great example of the Flaw of Averages in marketing. For some businesses, this curve will also look unusual, for example it might have a finite end – beyond a certain point you can’t acquire any more customers at any ‘price’ (cost per acquisition), because there aren’t any more in the market; or there might be step functions where beyond a certain volume of customers, CPA increases very significantly. How much to spend on marketing - the ‘demand/supply equilibrium’ for marketing I’ve asked many management teams: ‘if you could buy customers off the shelf at Tesco, what would you be prepared to pay for them’ – in other words, the maximum CPA you would pay. This is a difficult question to answer, but we can use our demand-supply thinking here to attempt it. If you’ve already got an understanding of your ‘customer supply curve’, then there are two factors to consider: Your expected customer lifetime value over a time horizon that makes sense for your business & how to overlay this on your supply curve to understand the profit maximising average CPA; and Other constraints for your business, primarily the maximum cash that you are able to temporarily invest in customer acquisition, for example as customers may be loss making for an initial period before they ‘pay back’ the cost of acquisition (this isn’t the same as your marketing budget but rather in finance terms the working capital required to fund marketing activities). Once you have these inputs, you can work out the cost per acquisition you should target in order to profit maximise over your chosen time horizon. For example, let’s assume that customers generate on average £800 contribution before acquisition costs in year 1, and a total contribution before marketing costs over five years - their lifetime value - of £2,500. We can apply this lifetime value of £2,500 to each point on the customer supply curve, to work out how much overall profit we would make: Lifetime Value of Customer Cohort = (LTV per customer – average cost per acquisition) * Number of customers. When we plot this curve on the chart, we identify that the ‘profit maximising’ cost per acquisition is c.£1,650, which will bring us 7,100 customers. At this level, we will spend £11.6m on marketing and an annual cohort of customers will make £6.2m of profit after marketing spend over the five-year time horizon. Targeting a higher average cost per acquisition will lead to more customers but less profit per customer, and less profit for the cohort overall effectively meaning that each extra customer acquired beyond this point is loss-making. Now, clearly if average CPA is £1,650 but year 1 contribution is £800, these customers are going to be 'loss making' at first - and not every business would be willing or able to support this. Let’s assume that you (and your CFO!) are willing to temporarily invest up to £2,000,000 cash (working capital) in customer acquisition at any point in time. We can this constraint into a maximum number of customers at each level of cost per acquisition and plot it on our chart: Number of customers = Cash available/(Year 1 customer lifetime value – average cost per acquisition) The point at which the 'Customer demand curve' line that we've added crosses your customer supply curve reflects the average cost per acquisition you should target, given the cash constraint. At levels of cost per acquistion below Year 1 contribution of £800, you can see that the line doesn't appear on the chart as you aren't constrained by working capital at these levels in this scenario. In this *highly illustrative* scenario, you would only be able to afford an average cost per acquisition of £1,270, hence your cash constraint would limit your marketing spend rather than marginal customer profitability becoming negative. In this simple example we are looking at customer ‘breakeven’ over a full year, in practice you might think about this at a monthly level or an even shorter timeframe – but the takeaway is that often from a ‘demand’ perspective, it is often (but not always) the appetite of a business to invest in temporarily loss-making customers that will set a ceiling on the number of customers you are willing to acquire - in particular in business models with subscriptions or other types of recurring/reoccuring revenue. In reality, other constraints will also come into play, such as the operational capacity of your business to service any given volume of customers, or perhaps that your input assumptions around unit economics will change because beyond a certain point you would end up acquiring less attractive customers. How to put the theory into practice I’ve found that this way of thinking about customer acquisition is a helpful way to evaluate marketing strategy and make decisions, rather than something to be used as a precise ‘model’. As with much economic theory, the real world doesn’t always behave, input data will always be imperfect and relationships will change over time. But if you have a clear enough starting point of your current marketing effectiveness and customer lifetime value, you can apply this approach in a few areas, for example: Use the concept of the customer supply curve to identify and prioritise improvements to your customer acquisition activities, for example improvements to your conversion rate, demand efficiency eg PPC quality score, or renegotiating partnership terms; Calculating the overall impact of improvements to customer lifetime value and the resultant change in your maximum cost per acquisition, for example when considering investments that could improve lifetime value; Answering my favourite question for marketing leaders of ‘where would you spend your next [£1m]?’ by identifying whether simply having a greater willingness to invest in working capital for customer acquisition could allow you to increase the number of customers you acquire profitably; and Use this approach to zoom in on a specific channel, for example we’ve recently used this approach with a client to deep-dive into non-brand PPC. This helped us to highlight that their average cost per acquisition was well above the profit-maximising level, and a lower cost per acquisition / higher ROI could significantly increase business profitability. If you’d like to discuss how you can accelerate customer acquisition in your business, please Contact Us. All views expressed in this post are the author's own and should not be relied upon for any reason. Clearly.