Top 8 ways a CDP can make you a better customer marketer

Julian Berry, Director, UniFida
By Julian Berry, Director, UniFida

CDPs – Customer Data Platforms – are often just evaluated from the viewpoint of facilitating timely, relevant and personalised customer communications. Properly configured, a CDP can also hold a complete history of every customer interaction, from online to direct mail, opening up very valuable insights into customer understanding.

Here are the top 8 ways a CDP can help you better manage your customer marketing:

1. Measuring how each and every aspect of your direct marketing is performing.

Having every customer touchpoint in place leading up to each of your sales is a critical requirement for delivering customer journey-based marketing attribution. This works best when you have a scoring system in place that can share out the value of each sale across the touchpoints that lead up to it, according to the contribution they make. In this way, you can not only compute the value of each of your online and offline campaigns but also look at how different customer groups, for example, new vs. existing customers, are impacted by your marketing activities. And you can start to look at how each channel performs in different seasons.

2. Knowing the longer-term value of customers recruited through different channels and via different campaigns.

Longer-term customer value varies hugely across the different types of customers you recruit and different channels will attract different types of customers. So, assuming you know how a customer was recruited, you can start to understand what their longer-term value is likely to be. This can be problematical where several channels are involved in a single sale, but you can look at the longer-term value of all the customers gained via a particular channel or campaign. You can also drill down further and differentiate customers by other criteria, such as previous relationship with your brand, geography, or even age band. Understanding customer longer-term value allows you to set maximum costs for acquisition and get a better understanding of the returns from marketing investments.

3. Predicting lapse levels and lapse timing for subscription products.

Anyone selling a subscription product, whether it be an insurance policy or a magazine, will know how vital it is to recruit and retain ‘sticky’ customers. Fortunately, the data residing in your CDP should allow you to model retention with a great deal of accuracy. This is because you will be holding not only the payment records of each subscribing customer but also a great deal of information about them. There are several statistical methods for doing this, but we tend to use CHAID as it divides customers up into identifiable groups with different expected levels of longevity. Your historic data can also be used to show what proportion of your expected lapses are likely to happen each month, which can be of vital importance for cash flow planning.

4. Building customer segmentations to help you better understand the needs of different customer types.

Marketers need to simplify the problem of dealing with many different types of customer requirement. The proven way to achieve this is to build a customer segmentation that gives you a handful of groups for which you can devise different marketing strategies, or even different products and propositions.

There are many techniques for building customer segmentations, but we like to use one that allows you to allocate customers with relative simplicity into their correct segment, and also to find similar types of people outside of your own customer base. For customers within the customer base, criteria such as value, previous sales or enquiries, and types of merchandise they buy, often groups customers meaningfully. For customers outside the customer base, segments are often defined by, for example, affluence or age band. Once the segmentation structure has been developed your CDP will allow you to allocate each customer to a segment and plan your communications strategy accordingly.

5. Managing all your GDPR consents in one place.

Customers deposit their consents in many different places. They may unsubscribe from one newsletter, opt-in to another, decline cookies on a website but approve receipt of customer marketing when placing an order. A marketer has to establish order in what is often a very untidy consents landscape and then define clear communications rules about what can be sent to whom on which pretext.

Your CDP is the one place where, through identity resolution, consents can be bought together and organised and rules about who can get which communication established. The CDP can also provide most of the materials for fulfilling Subject Access Requests, as well as manage anonymisation of data when the right to be forgotten is exercised.

6. Planning business development based on a customer value model.

Businesses need clarity on the growth and quality of their customer base, not least to understand how to split the marketing budget between acquisition and retention marketing to meet business objectives. Your CDP will hold a record of the historic value contributed by each individual customer and you will know what that amounts to in any historic calendar year. It will also tell you what percentage of customers recruited in previous years typically order in the current period. Using this information you can, with reasonable accuracy, predict what value, for example, your customers recruited this year will contribute during the next year and how this will be distributed month by month.

You will also know how your new customer recruitment usually lands month by month, and the value new recruits contribute in the period from when they were recruited to the end of the year. Pulling all this together you can calculate how many customers you will need to recruit in a future time period to meet a specific overall sales target. We call this the customer value model, all made possible by data held in your CDP.

7. Providing data for building response and upsell propensity models.

Predicting response by different channels can save a considerable amount of the marketing budget, enabling marketers to avoid activity that will not produce a strong return on investment. To build a predictive model you need a target variable, like propensity to make a second order, as well as predictor variables, which are facts known about the customers – in this case, both for those who buy the second product and for those who don’t.

The role of the CDP is to provide this data to the data scientist, or the AI tool, which is going to build the model. But as well as providing the data that allows the predictive model to be built, it also provides the data that then allows every customer to be scored up with a probability of doing whatever is being predicted. Indeed, without a CDP, developing and using propensity models for marketing is made very much more difficult.

8. Recruiting customers to join research panels.

Many companies like to maintain continuous panels of customers who have agreed to answer market research questions, usually in exchange for some value given back to them. The CDP can provide randomly selected customers for recruitment to these panels, as well as managing the exercise of sending them questionnaires and recording their responses. Customer panels are very much simpler to manage if you start with a CDP already in place.

Overall, a CDP should be seen as an essential component in the complex process of maximising your customer revenue through improving your customer marketing.


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