It’s not a wholly new notion that customers today expect to be understood as individuals, rather than groups or segments. They anticipate that companies will reach out to them in the ways and at the times they prefer, with relevant and helpful content that responds to their real-time wants and needs. Adam Baker, MD, Sociomantic, (pictured below) argues that in order to deliver this highly personalised experience across multiple devices and channels, marketers must invest in a robust customer relationship management system, which fits well within a programmatic environment, as doing so enables brands to react to, and participate in, the increasingly multichannel ways in which their customers are living and shopping.

Brits are predominantly digital shoppers with 80.4 per cent online shopping penetration. America follows closely behind at 79.1 per cent. As these figures climb, the margin of consumers who haven’t yet shopped online continues to shrink.

Thus, an abstract but no less realistic situation presents itself: what will happen when online shopping penetration hits saturation point?

Put differently, as there may be increasingly fewer new customers to be had, how can brands retain and grow spend from existing customers in order to remain competitive?

Winning loyalty is critical, and CRM innovation is a business’s key to achieving this. However, in order to mirror the shift we see in shoppers’ habits—from physical to digital, across a plethora of online channels—we must also see a shift in marketers’ mindset towards CRM.

To be clear, it’s not just about achieving loyalty in the traditional sense; it’s about understanding each consumer’s potential value to the brand, both as a customer and potentially as an advocate. Understanding the customer lifetime value (CLV) will benefit a brand’s CRM strategy in the eventual age of peak online shopping penetration.

CLV as the CRM of Tomorrow

If we’re to address CRM innovation, we need to talk about customer lifetime value. CLV is a customer’s net worth during their relationship with a brand, and it’s the essence of tomorrow’s CRM strategy for programmatic.

While a large customer base is often indicative of a brand’s success, how healthy a company actually is should rest on its ability to retain customers and nurture its relationship with them. In today’s market, a high CLV is desirable because it offsets the costs of further customer acquisition, thus supporting sustainable growth.

The best option available to most marketers is to identify their customer segments (CRM) by value (CLV), and target each of them in the most effective, cost-efficient way. By having CLV inform CRM segments, marketers are able to take their programmatic display advertising to the next level.

Programmatic creates the possibility to adjust the pricing and the messages suited to each customer profile. In doing so, brands are able to reach out to their ‘best’ customers—those most profitable, with a higher CLV score—whilst still targeting other existing customers and potential new shoppers in a personalised manner.

Measuring CLV for Sustainable Growth

It’s time to throw throw another acronym into the mix: RFM. The RFM model is most often adopted for measuring CLV. It identifies events along a customer’s journey when value is created: recency (how recent was the interaction?), frequency (how often does this happen?) and monetisation (what’s the value of the margin combined with the return rate?).

This measurement approach is based on the Pareto principle, or 80-20 law, which claims that the greater portion of your business (80 per cent) comes from the lesser few (20 per cent) of your customers. Therefore, when CLV is calculated, marketers are able to differentiate their high-value consumers from lower-bracket custom. The resulting action is two-pronged: nurture customers with a higher CLV, whilst steering the lower-value groups into the higher CLV category.

Recency and frequency can be determined by web analytics, and is fairly easy to measure. What’s often most difficult to determine in CRM deployments is monetisation. For example, factors like data warehouse accessibility is a necessity and often has to be custom-built for the enterprise in question.

To assess monetisation, marketers must be able to calculate the profitability of each customer on a per user basis.  And this calculation needs to work out the value of margin on purchased products combined with any outgoing costs to process returns.

Let’s consider the “Topshop party buyer” persona. This is a customer who scrolls through the dresses, the shoes and the accessories for a whole new outfit, top to toe. The shopper buys an entire outfit at a large expense, and then takes advantage of free returns in order to send the items back, tags re-attached after an evening out on the town. Marketers who only measure ‘Recency’ and ‘Frequency’ would categorise this individual as a high-value customer and would therefore invest more to market to them.

However, if the return rate were factored into the monetisation score, it’d be clear that the “Topshop party buyer” actually costs the retailer— resulting in a waste of marketing spend.

Driving Programmatic Strategies Forward

Because CRM is often transactional, there is a need to tie CRM data to these marketing interactions to measure their true performance. Brands that have their CRM data in order will be able to build customer profiles or segments to drive their programmatic strategies forward. They will be able to focus their investments on the customer groups, or even individuals, with the highest potential for revenue growth in the long term.

By using RFM to determine CLV, the retailer can create dynamic customer segments to encourage the growth of a customer’s CLV. Clusters of customers with similar CLVs can form CRM groups, which can then be used for granular-level targeting. Programmatic lends itself to the possibility of adjusting the pricing and messaging to each customer profile. A shopper who spends little but shops frequently is met with a different tactic versus the customer who goes for the high-ticketed items, albeit less often.

Linking programmatic with a CLV-informed strategy for CRM data seems the logical extension to satisfy consumer expectation during the next digital shopping stage. Tomorrow’s digital climate will have delivered the maximum customer base a brand can achieve. By focusing on growing CLV now, marketers will be well equipped for an ad tech prediction: peak online shopping penetration.