A proven framework of how leading companies create success with customer journey analytics

With the proliferation of digital channels, there is more and more information about customer needs and their attention. This information provides for the first time the data to monitor the full journey a customer goes through. Now, we can even understand the behavior of a potential customer before they make a purchase. Or, understand their post-purchase behavior: in terms of usage or product evaluation. Recently, VSBfonds and MIcompany identified an opportunity to increase the yearly turnover of the biggest theatres in the Netherlands by more than 100%. While very significant in terms of impact potential, there are also important pitfalls when opportunities are not linked with value creation. By understanding how value creation occurs throughout a customer’s entire journey, companies will get actionable and targeted insights for real impact. As such, they will be able to better identify how to intervene in their customers’ journeys.

Companies struggle with building relevant insights in their customer journeys

It has become standard practice to monitor and manage the journey of your customers across all touchpoints you have with your customer. Although standard practice, still most companies we speak with struggle to drive tangible impact along this journey. In our experience, the lack of impact is not driven through insufficient commitment to change their customer interaction. Instead, we see our clients with enormous amounts of journey data, but lack having the right insights in their customers’ journey. So what is often driving this problem with gaining the right insights?

1. Fragmentation leads to small impact. Companies often forget defining the biggest impact themes. Instead, they launch large analytical efforts, with detailed analyses to fully grasp how their customers behave along their journey. And as a result, they are overloaded with many, but small and detailed customer journey insights that provide marginal opportunities for impact. For example, based on detailed insights about differences in funnel conversions, companies start to invest in A/B testing in a manual manner. One of our clients had website pages with no more than 100 visitors per month that could drive churn. Making the improvement through targeted and manual analysis in these website pages, the company could add 5-10 customers per month. Clearly not enough to fund the analytics team. At the same time, this company invests millions of euro’s in Google AdWords advertisements. A 25%-improvement in Return of Investment on optimizing this spend, would easily lead to a million-plus profit opportunity.
2. There is no link with value creation. Business leaders are still used to optimize their campaigns on how many customers they convert. However, typically we see strong negative correlations between conversion and value creation. For example, detailed analysis of a marketing campaign shows that customers from a certain region and with a certain education-level respond better than other segments. By targeting this segments, companies can improve their campaign conversion. Often, this segments have a negative or low value. There can be multiple reasons for this effect: high conversion-segments were offered a low price compared to market prices, high-conversion-segments have a high first-year-churn because they switch every year or high-conversion segments have a high probability of default because the competitors do not accept them. Therefore, for many campaigns, conversion optimization along the customer journey will lead to value destruction, not creation.
3. Departments are working in silos. Companies often separate the online customer interaction, with the traditional off-line channels, such as shops or call-centers. This is of course not how your customers look at their decision journey. The customer sees the internet as just one of the channels, and is very comfortable with using many touchpoints across multiple channels throughout their customer journey.
4. As a result, we see that optimization of only the online channel is often suboptimal to improve customer behavior along the journey. For example, analysis showed that there is almost no conversion on visitors who enter the website through Google AdWords. A logical first reaction is to stop the investments in Google AdWords. But by looking at the entire customer journey, we found out that the customers who entered the website through Google AdWords asked help from a call center agent to finalize the transaction. So, stopping the Google AdWords investments would likely lead to a reduction in sales.
5. Companies fail to unlock online data. Many businesses start with online Data Analytics, through collecting their online data in an aggregated manner. For instance, they analyze their online performance in terms of total number of visitors or total number of sales. Because this data does not provide specific insights about the individual customer journey, it fails to pinpoint the right opportunity for each customer. For instance, you would consider how to improve the information about your products to customers to web-site visitors at the beginning of their orientation process. But for visitors that have trouble finalizing their transaction, you might want to stream-line the payment process.

The Customer Journey Value Cycle (CJVC) is the foundation to pinpoint initiatives on impact

To overcome the above pitfalls, MIcompany developed a framework to help our client’s structure and build the most important insights when they start managing their customer journeys. Our framework, the Customer Journey Value Cycle framework (see Figure 1), is built on two principles:

6. Companies can only increase the impact of customer journey analytics if they understand value creation along a customer’s journey (the core of the framework).
7. Value is created across the customer’s entire journey, but every step in the journey has different opportunities (the outer circle of the framework).

Principle I: Understand the impact of journey path changes on value (the core)

Based on their needs and attentions, customers show different behavior over time. When customers show changing behavior, we call this a journey path change. These journey path changes are crucial because value is created or destroyed at the moment they occur. Before we can start modifying journey paths, we need to understand how value is created along each customer’s journey. This can be measured in two dimensions: (1) Value to the Firm (often measured by Customer Lifetime Value), and (2) Value to the Customer (which is often measured by a customer satisfaction metric, such as the Net Promotor Score). When we talk about value creation along the customer journey, we are talking about both dimensions.

For example, some offline customers are migrating (the journey path change) to self-service online bots. Before we can decide whether we should stimulate this behavior or we should offer an alternative, we want to understand the impact of this journey path change on value. Typical questions we should answer in order to create this understanding are: what is the total cost reduction?, what is the impact on sales and acquisition value?, are customers satisfied with the answers they get? When we answer this kind of questions we can start with thinking about how we should respond on this journey path change.

Principle II: Create value across the journey (the outer circle)

Once we know how value is created during the journey, it is critical to record and understand the full customer’s journey history. Only with data on that fully history, we start building an understanding of behavior, and its underlying needs. Without having the full picture, similar journeys have very different underlying behavior and meaning. For example, three visitors may be viewing the same webpage. One visitor may be looking for product-conditions regarding a cancellation, one may be trying to answer a short question about the product, and the other visitor may be on the website to buy the product.

Combining the two principles will guide leaders to build a full perspective on behavior, and how that behavior translates to customer value creation by being relevant for the individual customer (personal relevance). For example, a high-value customer with an easy question can be served by an online bot. When the bot is able to effectively answer the question, this will affect customer satisfaction positively and lower call center costs. At the same time, a high-value prospect who is visiting the website for the fifth time may need help from an experienced call center agent to finalize the transaction. This example shows that, if we really understand the individual customer journey and combine this with a deep understanding of the impact on value, we are able to offer the best service to every customer. As a result, this will increase value: both for the customer as for the firm. To illustrate the potential from having the right insights in customer journey analytics, we share four case examples that drove impact from insights on the CJVC.

1. Improve Acquisition ROI by Introducing a Google Keyword Bidding Strategy

Especially at the beginning of the customer journey, customers and prospects use multiple touchpoints for orientation. By following these ‘prospects’ through their journey we found that more than half of all prospects enjoy more than three touchpoints before they actually buy a specific product or service. At the same time, marketers still allocate their budgets on each media channel separately, paying for each touchpoint.

For example, our analyses showed that for some customers marketers pay three times the fee for Google AdWords, two affiliate fees and one aggregator fee. We began to wonder if we should spend less money on Google or look for an alternative payment structure. To address this opportunity, we needed to understand the total value creation for each Google keyword. By using an advanced Markov Attribution Model, we were able to measure how Customer Value creation was linked to each Google keyword used by the customer in their journey. By combining this attributed value with the total acquisition cost per keyword, we were able to calculate a return on Investment for each keyword (see Figure 2).

As a result, we defined a new Google keyword bidding strategy. We decreased our bids for keywords with negative value creation, and increased our bids for some keywords with positive value creation, taking into account the current position of each keyword in the AdWords ranking. By implementing this new bidding strategy, we expect a Return of Investment improvement for our Google expenses by more than 50%.

2. Increase Online Repeat Sales by Introducing Online Product Bundle Recommendations

At one of the largest theatre in the Netherlands, we found out that 96% of the online customers only bought tickets for one theatre performance at a time. But by analyzing the online customer behavior on the website before and after a sale using the journey history, we found out that 59% of all online customers visited a webpage for another event. Therefore indicating a much richer customer preference set for events, an insight which had not been targeted before.

Moreover, our insights in value creation showed that driving repeat visits is the most important value driver in the theatre business. Combining again both a view on value creation, with the detailed data on customer orientation, we concluded to improve recommending follow-up events to customers. But this time, the recommendations would be based on detailed insights in the customer journey. Through discussions with marketing and the online technology specialists, we concluded that we should bundle products based on personal preferences. We launched a new initiative, ‘Bundle This,’ where we offered every customer a personalized product-bundle based on their previously visited website pages and online website behavior

The results of the first implemented pilots show a significant uptick in the percentage of customers buying multiple tickets. The roll out potential of this initiative is more than two million euros.

3. Reduce Leakage from Website to Call Centre

At a financial services firm, we had some indications that a significant share of incoming customer service calls was caused by incomplete information on the website. Once we integrated the online website data with the offline contact center data, we were able to analyze customer behavior on their journey across channels. For instance, we were able to pinpoint which website pages resulted in service calls within a minute after visiting that specific part of the website. By performing a qualitative analysis of those webpages with a high leakage, we concluded whether the information where customers were searching for was not available or just not clear. We changed the content of the webpages, and – because of the real-time availability of the data – we were able to monitor, evaluate and improve our changes on a daily basis.

The results of these intervention in the customer journey lead to more than 80% of calls from specific web-pages, and a more than 20% increase in NPS scores. We estimated that further improvements in the web-site could lead to more than 15% reduction in call-center expenses within a year.

4. Reduce Churn by Predicting Online Customer Behavior

We analyzed the website behavior of ex-customers before they churned, and discovered that more than half of the outflow had visited the ‘closing my account’ section of the website in the month before outflow. Although this insight gave us a lot of ideas, we lacked a perspective on value creation.

More specifically, is not a question of how people behave in their journey paths (in this example, the change is cancellation). What matters is the impact of behavior change on value creation. Therefore, we modelled the value loss from customers that had churned. We first came to the conclusion that a visit to certain subpages and specific search terms, such as ‘my invoice’ and ‘how to cancel my contract’ are strong predictors for churn. Secondly, we found out that the majority of the churned customers were our high value customers because they had a relatively high product usage before they churned. This was a very important insight, because now we know that a reduction in churn leads to value creation and not to value destruction.

We defined two opportunities to bring these insights into action. First of all, we could enrich the existing churn prediction models with website behavior and customer value in order to improve the results of our current pro-active churn reduction program. Secondly, since we knew that for specific paths the value loss was substantial, they could afford to retarget these customers with a personalized retention offer based on their value, either on our own website or websites from third parties. These two opportunities had a total potential of almost 10 million euro’s customer value per year. This was really a breakthrough, because these insights along the customer journey gave an answer to a churn problem which already exists for years.

Closing thoughts

As the above examples illustrate: a thorough understanding of value creation across the entire customer journey is the fundament for improvement. MIcompany’s CJVC framework ensures not only journeys get improved on conversion, but that real value creation is achieved through customer journey analytics.

Moreover, our case experience has shown major impact potential in this field. At some theatres, who are in their early stage of sophistication on journey analytics, we estimated that sharper insights on the CJVC could even double yearly revenues. At more mature clients, we see often upside potential of more than 10% of revenues. For example through smarter targeting online media budget (case example 1) or reducing leakage from the website to call (case example 4). Our question to you is: Are you ready to move to the next level? And build individual customer insights on value creation along the whole customer journey?

1. A/B testing is a method of comparing two versions of a webpage or app against each other to determine which one performs better.
2. The Value Cycle should be modified depending on the branch and business dynamics.
3. Affiliate marketing is a type of performance-based marketing in which a business rewards one or more affiliates for each visitor or customer brought by the affiliate’s own marketing efforts.
4. A website that aggregates products from numerous companies and compares them on for example price or reviews
5. The Markov Attribution Model divides the customer value to all customer-touchpoints based on the importance of that specific touchpoint in the journey.