Search Results

The group stages of Euro 2024 are over. And, as promised, the update to our Euro 2024 prediction model has arrived. I’m young enough to have enjoyed a period of remarkable optimism surrounding the England football team. Memories of the disappointment of our Euro 2016 exit against Iceland had been firmly eclipsed by the fervour of 2018, 2021 and 2022. Up until the last 3 weeks, where the England football team collectively decided to abandon ambitions of winning an international tournament in favour of raising the nations average blood pressure as steeply as possible. But, my word, at 7pm on Sunday evening, was it all worth it. We haven’t quite developed LeadScorer (our pipeline prediction tool) to the point of being able to predict 95th minute bicycle kick winners. Yet. But, we have got a data-led prediction for how things are going to pan out from here, so if you would like to know if there is more frustration ahead for England fans, or if that magical moment could be the start of something special, read on. If you would like to see how leadscorer predicted the outcome of Euro 2024 before the group stages had commenced, you can check it out here . RECAP - How have we done it?   At Coppett Hill, we’ve developed a tool called LeadScorer, which takes a series of prospect attributes and behaviours, and predicts their relative likelihood to purchase. This can then be deployed to prioritise customer outreach and get a feel for overall pipeline value. Essentially, we took our LeadScorer tool, repurposed it to use the result of every international football match since 2016 and accompanying team attributes as training data, then generated an expected result for each possible fixture, and consequent tournament progression. Since the conclusion of the group stages, we’ve included results from the past 3 weeks in our training data, and, as much as it pains me as an England supporter, introduced a recency bias to simulate form/momentum heading into the knockout stages. As before, I’ve taken the liberty of furnishing this article with a series of AI generated images. Also, as before, please do not take this article as any form of gambling advice. Obviously.   The group stage – was our model any good? Given that LeadScorer was developed for a very different purpose, we were pleasantly surprised with the accuracy of our model. England were predicted to beat Serbia by a single goal, before drawing 1-1 against Denmark and squeezing past Slovenia by two goals to one. Scotland were predicted to suffer defeat against Germany before securing hard-fought draws in their remaining fixtures – this almost came to fruition, if not for a 90 + 10’ goal for Hungary in their final game. Not bad. I’ve made the executive decision that only the results of groups A, B and C are relevant when assessing the accuracy of our model so far – I’ll be taking no further questions on this matter. So, what happens next? As we all know, England are drawn against Slovakia in the round of 16. And, as we all know now, Bellingham steps up to the plate after 95 minutes to deliver one of the all-time great England moments, with the score eventually finishing at 2-1. Funnily enough, the model knew this too. I’ve included a snip of the SQL output to maintain a level of credibility here. Elsewhere, admittedly, we didn’t have Switzerland brushing Italy aside to make it through to the quarter finals. In the interest of keeping this as relevant as possible , we are going to manipulate the output a little to see England meet Switzerland in the quarter finals, as will be the case this Saturday coming.   The quarter-finals Crunch time. An underwhelming England take on an exciting Switzerland side, buoyed with the confidence of knocking out holders Italy in the round of 16 . Gareth Southgate’s men know that the level of performance simply has to improve, or they will be faced with another quarter final exit. And maybe, just maybe, the drama of the last 16 awakens something in the England squad, as Jude Bellingham once again sends England into ecstasy by delivering when it matters most. Final score: 2-1. Elsewhere, the Portuguese knock out France, and the Netherlands see off dark horses Austria.  Here is the image of Jude Bellingham being England's saviour, securing a 2-1 victory in the quarter-finals of Euro 2024. The semi-finals The Netherlands have struggled with expectations at this tournament, and England have steadily built momentum. However, as any football fan knows, a victory against a nation with such a level of football heritage can never be taken as a given. And yet, the frustration of the group stages disappears further into the rear-view mirror, as England produce their most assured performance yet to book their place in the final with a 2-1 win. Liquid football. Elsewhere, as in our previous set of results, Spain eliminate Portugal in the other semi-final. Here is the image capturing the excitement and expectation building in the nation after England defeats the Netherlands in a game of liquid football. The final England succeed in banishing their early tournament woes to meet a Spain side who have impressed from start to finish. In our previous set of results, England fell at the final hurdle to lose on penalties – can we go one step further this time? No – this time around we just lose within 90 minutes. Sorry. Again. Here is the image of Jack Johnson, reflecting on the machine learning model he created predicting England's loss against Spain in the Euros final, with a subtle mix of disappointment and satisfaction that the recency bias introduced to the model has had the expected effect. We like to hope that this prediction will prove to be wrong – we think the model behind LeadScorer is significantly better at predicting a likelihood of a prospect to purchase than football results. If you are interested in how we can use LeadScorer and our other tools to help your business , please Contact Us .

The ability to win ‘new client logos’ is one of the most important predictors of future growth for a B2B business. The problem is, assessing this ability isn’t always straightforward, even though there is often no shortage of data available. Deciphering the drivers behind new client logo acquisition can involve navigating siloed datasets, accommodating inconsistent CRM entries and picking apart complicated financial models. More often than not, in our experience, all of these are necessary when forming an estimate of the achievability of a business plan. Suppose you are an investor, developing your own assumptions for new logos and sales team resourcing before your next trip to the Investment Committee. With such a breadth of data potentially available, choosing where to start can be an intimidating prospect. At Coppett Hill, we’ve developed a set of approaches which use our suite of proprietary tools to assess new client logo acquisition, which we use when undertaking Value Creation Due Diligence. We’ve come up with the five charts that consistently top the list when looking for insights on a new business sales function. 1.      Pipeline value over time This may seem obvious, but however sharp a sales team is further along the line, the ceiling for their performance is determined by the number/value of leads entering the very top of the funnel. Management teams can often find this hard to provide unless they’ve been ‘snapshotting’ the data regularly, or have old board packs containing the data. We’ve developed an approach to rebuilding historical pipeline value by day based on CRM data. So, what do we look for? Is there a positive trend, that ties in with the commentary provided by Management? Is there evidence of seasonality in this data? If there are big changes / spikes, could these be related to the arrival of a superstar member of the marketing or sales teams or a new product launch? Has the pipeline been impacted by the wider economy, or a change in regulation within the industry? The value of the pipeline prompts questions about the overall context in which a new business sales team operates and is essential to underpin the understanding of more granular analysis. If the business has a longer sales cycle with more defined stages in the customer journey, it may make more sense to consider weighted pipeline, where a percentage likelihood of conversion is assigned to a prospect depending on how far along they are in the sales cycle. 2.      Historical conversion rates Looking back historically, there is merit in considering conversion rate measured by both when opportunities first enter the pipeline (some of which may still be open, distorting the conversion rate) and when they are closed. Both are important when forming a view of just how much of a current pipeline is likely to be won. One especially important point here – conversion rate is only a useful metric when considered within the context of CRM use. Validating the quality of pipeline data can establish this context – if conversion rate is very low, is this a reflection of the effectiveness of the sales team, or are inappropriate/low probability opportunities being added to the CRM? If it has changed historically, does this reflect a change in CRM use? It’s also worthwhile to analyse conversion rate at several different levels – a business may have had more success winning one type of opportunity than another. Cutting conversion rate by customer type, product/service opportunity and region can give a picture of sales momentum heading forward in to the vital first year of a private equity investment. Contrasting a value-weighted conversion rate with a volume-based conversion rate can shed some light on the opportunities that a sales team are most adept at winning – is this consistent with the business plan assumptions? 3.      Pipeline/forecast accuracy Just how accurate have previous forecasts of conversion percentage at each stage of the funnel consistent with actual outcomes? Is the ‘weighted pipeline’ reliable? We use the log of changes stored in the back-end of a CRM system to identify all historical opportunities that have reached each stage of the pipeline, and how many go on to eventually convert. The conversation triggered by the presentation of this chart can quickly surface gaps between management’s idea of what drives sales performance, and what the data shows. More often than you may think, the assumed conversion rates are the defaults used by the company’s CRM system rather than a result of considered historical analysis! 4.      Attribution analysis Where have the last 10 logos the business has won come from? Performing analysis on the origin of won customers is essential for understanding which demand generation channels should be prioritised for further investment, which should be ‘turned off’ and ensuring that marketing and sales resources are allocated effectively. You would be very lucky to have a ‘Source’ field that is well-populated and reliable in the CRM, so we often generate a list of recent wins and talk through each one with the marketing and sales team (and sometimes the customers themselves) to define the source. The correlation between a marketing team’s view on attribution and that of the sales team can give a high-level indication of the relationship between these teams – are they well integrated, or do they hardly speak to one another? 5.      Individualised sales metrics All of the charts we’ve covered can be isolated down from an aggregated view to give a view of the individual performance of each salesperson. Well-organised smaller teams may exhibit spikes in conversion/sales cycle etc due to each member of the team being responsible for different types of customers in their individual niche. In larger teams, with many individuals in essentially the same role, these metrics and their accompanying incentive structures may reflect the relative performance of each individual. Is there a consistent ‘ramp’ profile of new joiners in the sales team which speaks to a quality hiring and onboarding process? Have underperformers been addressed? Are there any superstars which could represent a risk if they were to leave? A view of these key metrics by individuals can inform all of these questions. As an investor or operator, there are countless ways to assess a new business function, and this approach is inevitably going to depend on the unique product/sales process involved. We think in almost all cases, the charts we have listed are a good starting point. If you’d like to discuss how you can better understand your new client logo acquisition, please Contact Us .

I’ve been doing some work recently on our LeadScorer tool, which takes a series of prospect attributes and behaviours, and predicts their relative likelihood to purchase. This can then be deployed to prioritise customer outreach and get a feel for overall pipeline value. However, as cases of Euros fever in the Coppett Hill office increased in severity, the lightbulb flickered to repurpose this tool to answer the question on everyone’s lips. Is it coming home? And just like that, Project World In Motion was born. How have we done it? Purists would say that the beautiful game is named so for the fact that the outcome of a game is determined by so much more than historical performance, player form, home advantage etc. We, at Coppett Hill, have chosen to entirely disregard this point of view for the sake of enjoying some of our niche brand of nerdy fun. Essentially, we took our LeadScorer tool, repurposed it to use the result of every international football match since 2016 and accompanying team attributes as training data, then generated an expected result for each possible fixture, and consequent tournament progression. Early iterations of our data structure/model produced some interesting results. In one early example, Scotland beat Germany 7-0 in the opening fixture, providing a textbook example of why you should always common sense check your outputs - sorry Scotland fans. With some iteration, we arrived at a set of (depending on your point of view) less ridiculous results, and the golden question was answered. I’ll be updating the model following the conclusion of the group stage - stay tuned. In the spirit of this being a bit of fun, I’ve taken the liberty of furnishing this article with a series of AI generated images (the description in italics is also AI generated!). Before we get started, this does not constitute any form of gambling advice. Obviously. Now, let’s get into it. The group stage In true England fashion, the tournament begins with nervy 2-1 win against a tough Serbia side. Bringing back memories of the Euro 2020/21 semi-final, England second group game with Denmark ends at 1-1 after 90 minutes. Finally, England manage to squeeze past Slovenia 2-1 to secure top spot in group C on 7 points. The defence is slightly more porous than we might have hoped, but the ability to grind out results when delivering underwhelming performances is giving rise to a mood of cautious optimism around the country. Scotland scrape through to the round of 16 by the skin of their teeth with a total of 2 points at the group stage, losing to Germany before securing hard-fought draws in their remaining 2 fixtures. Here is an image capturing the atmosphere of cautious optimism around England ahead of Euro 2024. Fans are gathered in iconic locations, dressed in England kits, waving flags, and showing support for the national team, reflecting hope and anticipation. Enjoy this depiction of the hopeful mood! The round of 16 England produce an assured performance against Turkey to come to a comfortable 2-1 win at the round of 16. Elsewhere, it is the end of the road for Scotland, who fall short against Belgium. Here is the split scene depicting England's assured performance to win against Turkey and Scotland falling short against Belgium. The image captures the contrasting emotions and outcomes of both matches. Enjoy the visual representation of these moments! The quarter finals The quarter finals arrive – the backdrop for so much heartbreak over the years for England fans. Facing none other than holders Italy, England produce a 2-0 win to book their place in the semi-finals, and even the most pessimistic of fans begin to question whether this could finally be our year. Elsewhere, tournament favourites France are eliminated by Belgium. Here is an image of an extremely pessimistic England football fan, with a deeply sceptical expression, slumped posture, and arms crossed. The atmosphere is filled with doubt and resignation, capturing the hesitant and almost reluctant optimism. The semi finals Faced with the prospect of a star-studded Belgium side, the nation holds its breath. England stars trade blows with their domestic teammates, pushing hard for a late winner but unable to separate the deadlock in ordinary time. With the prospect of penalties looming, captain fantastic Harry Kane steps up to win the game late in added time. Absolute limbs. Here is the image of Harry Kane scoring a penalty with many extra limbs, further enhancing his striking power. The dramatic scene captures the excitement and tension of the moment with the packed stadium and cheering fans. Enjoy this surreal depiction! The final It all comes down to this. 90 minutes to end 58 years of hurt. A young and impressive Spain side stand in the way. And we lose on penalties. Sorry. Here is an image of Jack Johnson, looking sorry and regretful for creating a machine learning model that predicted England would lose the Euro 2024 final on penalties. The scene captures the remorseful expression and office setting with England football memorabilia. We like to hope that this prediction will prove to be wrong – we think the model behind LeadScorer is significantly better at predicting a likelihood of a prospect to purchase than football results. If you are interested in how we can use LeadScorer and our other tools to help your business, please Contact Us.

I once sat in on an expert interview at the start of a market research project, as a silent observer. I had to bite my tongue as the interviewer diligently followed the interview guide and missed several opportunities to dive deeper into a nugget of insight that the expert had touched on. As a junior strategy consultant, leading these expert interviews was a core part of my role so I’ve led hundreds of discussions and probably made every type of mistake along the way. Qualitative research can be hugely valuable in providing a rich and nuanced understanding of your market and customers, whether standalone or alongside a quantitative research approach. However, if not set up correctly, it runs the risk of missing the below the surface details that are most useful and actionable. I want to share my tips for getting the most out of a qualitative research exercise. This guide is focussed on market expert, competitor and customer research interviews to inform strategic choices and marketing plans. We will cover focus groups, which are often used for brand positioning, product/service design and user feedback, in a subsequent article. Some example use cases for this type of research might be: Refining your proposition and ICP [link]: Getting a better understanding of your customers’ decision criteria and for which types of customer your product or service is most differentiated Entering a new geography: Speaking to potential customers to understand if and how customer needs differ in that geography, and therefore how you may need to adjust your product, technology, sales channels, Investments and acquisitions: Getting an overview of a market, the competitive dynamics and how a potential acquisition target is currently positioned and where the opportunities are for them. Pricing strategy: Understanding customer’s perceived value, key decision factors, willingness to pay and competitor pricing models to inform your pricing strategy. Here’s my checklist for great qualitative research interviews: Planning your research interviews Get really clear on the objectives. You will only be able to cover a small number of subjects in each interview, especially if you want to have time to dig into the details Start with hypotheses. It's worth spending the time upfront to get really clear on hypotheses you want to test rather than broad subject areas. e.g. ‘We think xyz security feature is going to be more important in this geography due to regulatory laws’ rather than ‘What features are customers interested in?’ I’ve found it really useful to run a workshop with the key stakeholders from my client to shape and refine these hypotheses up front. Focus on the hypotheses that will drive decisions and actions. For example, if you are entering a large and growing market where your company will have a tiny market share, you don’t need to spend ages understanding whether the market is growing at 5% or 10%. Focus instead on understanding your initial target niche and relevant routes to market. How many do you want to do? The right answer will depend on the topic and how many different audience segments you want to cover. I usually find after 4-5 interviews within a topic and segment, you usually start to hear the same themes. I usually aim for 15-30 interviews to get a good overview across a range of interviewee types (e.g. Enterprise customers, small customers, subject matter experts, competitors). Sourcing your interviewees Make sure you source the right people to speak to. If you are using an expert network, it is worth spending the time with them to get the right interviewees; it often takes a few iterations. Some things to think about: Do you want to have a sample across each of your key segments e.g. SMEs, mid market, and Enterprise customers What role will best be able to speak to the subject area and level of detail that you are looking for? For example, if your client sells a MarTech product, Marketing Directors are more likely to speak to key decision criteria, whereas marketing managers who use the product day-to-day may have more specific insights on features and pain points. Use screening questions to make sure you get people who can speak to the specific topics you are interested in, as job titles can mean very different things across organisations. Existing customers can be a great source for interviews and are likely to be more honest and less biased if speaking to an external third party. I’ve found that customers are usually quite happy to make time for interviews, especially if it’s framed as an effort to better understand and serve your customers. Here’s some example wording you or your client's team might use to request these interviews: “We have partnered with [Coppett Hill] to support us with [xyz project]. As part of this they are conducting a series of interviews aimed at gaining a deeper understanding of our customers’ experiences, challenges and needs. Your perspective as a [long standing/recent/valued] customer is incredibly important to us, and I was wondering if you would be willing to spare some time for a brief interview? The insights gathered will be instrumental in helping us tailor our product to better meet your needs. Your comments will be kept anonymous, and the insights only shared with us at a summary level. The interview would be scheduled at your convenience and should not take more than 30 minutes. If you are willing to participate, please let me know and I will coordinate with [Coppett Hill to set up the interview at a time that suits you best. Designing your interview guide Limit yourself to 6-8 question topics. I can admit to finding it hard to follow my own advice on this one, but you typically only have time to cover 6-8 overarching questions in an hour. This allows you enough time to get into the details within each topic and forces you to prioritise those which are most important. I have in the past split interviews into 2 groups, with a different focus for each, when I’ve had too many topics to cover in one session. Craft open ended questions. Design questions that encourage richer, detailed responses rather than simple 'yes' or 'no' answers. Sequence questions logically. Start with broader, more general questions to set the scene and ease in to the topic, before moving on to more specific lines of questioning. Iterate as you learn. Iterate your guide after the first 2-3 interviews and don't be afraid to keep iterating based on what you're hearing. You'll likely start hearing the same themes coming up and figure out which areas you want to deep dive on. Focus on real behaviour. As with survey questions, focussing on actual, recent behaviour rather than hypothetical situations or intentions is likely to get you a more honest answer. Collect hard data... Where relevant, it can be really useful to ask for quantitative data, even if you will only have a relatively small sample size. For example Company size (especially useful for segmenting insights across a large sample) I.e. revenue, # employees, growth rate Net Promoter Score to understand customer advocacy Pricing information ...but don’t over-promise how much you will gather. You may not have the time to gather this data in every call, and some respondents may decline to answer. However, sometimes conducting a large number of interviews is the only way to gather quantitative data. I once did a project where we had to speak to 170 Local Authorities across the UK to gather market data. This is an expensive approach to take, so use it wisely! Conducting the interviews Make sure the person doing the interviews understands the business and the context. I cannot emphasise this enough. If you have an outside provider conducting these interviews, it’s well worth the upfront time to educate them on your product or service and market context so that they can deep dive skilfully and pick up on subtle but important points. Follow the natural flow of conversation. Treat the interview guide as just that, a ‘guide’ not a set of instructions. If the interviewee brings up an interesting point, take the opportunity to follow the thread and ask follow up questions when relevant, rather than sticking rigidly to a question guide. Don’t stop at the first answer. Ask follow up questions and keep probing. Try to get specific details, and even better, real life examples. For example, most people will say price is an important decision factor, but ask them if they have recently or ever moved provider because of that? Then ask them to talk through the decision-making process for that change. ‘Tell me more...’ and avoiding the impulse to fill uncomfortable silences. Leaving a pause is very effective in encouraging interviewees to share more. Go beyond active listening. Don’t hesitate to take the opportunity to seek clarifications and make sure you’ve really understood what the interviewee is saying. For key points, it’s well worth checking ‘So I think what I’ve heard you say is…?’. Their clarification will often surface valuable insights that they hadn’t shared the first time around. Pay attention to nonverbal cues. Notice what energises them and where they show frustration, these are likely to be areas that are worth digging in to. Take thorough notes. If permissible, use recording software that will give you a transcription, if not then take detailed notes. I usually find it most helpful to take notes of the key points myself, then using the transcription to go back and fill in the details. An easy-to-use transcription tool I’ve used for note taking for video calls is Fireflies.ai. For very detailed or complex topics it can be worth having a second person to take notes so you can focus on leading the conversation. Try to structure your notes against the key hypotheses. This will make it easier to see key themes across a large volume of qualitative data. Don’t lose the details. Often the specific details and direct quotes are the most useful, especially for internal stakeholders. You might summarise these when presenting to the Board, but make sure to capture the details in a way that can be shared with internal stakeholders. Qualitative research can be hugely valuable in informing your strategy, and this checklist should help to ensure a high quality and actionable output. If I’ve missed any common pitfalls or items from your own checklist, please let me know. If you’d like to discuss how to run primaryesearch 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.

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.