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Digital personalisation at scale

Digital personalisation at scale

Digital personalisation at scale. Customers decide very quickly—in a matter of seconds—whether they like your marketing message. Provide something relevant and you’ve got a satisfied customer. Miss the mark, however, and they’re gone.

This issue of relevance in our era of instant gratification is particularly pronounced because consumers are bombarded with messages, most of which are off target. Personalisation—the tailoring of messages or offers to individuals based on their actual behaviour—promises to address this issue.

While many companies have been able to personalise with a few product lines or segments, most still struggle to scale across all the ways they engage with customers. Technology has an important role to play, and the tools to achieve it are developing rapidly. The real challenge is to transform the marketing organisation’s processes and practices to achieve the full potential of personalisation.

Done right, personalisation enhances customers’ lives and increases engagement and loyalty by delivering messages that are tuned to and even anticipate what customers really want. These benefits to the customer translate into benefits for the company as well. Personalisation can reduce acquisition costs by as much as 50 per cent, lift revenues by 5 to 15 per cent, and increase the efficiency of marketing spend by 10 to 30 per cent.

Through more than a hundred engagements over the past five years, we’ve found four steps that lead to successful digital personalisation at scale:

Take a journey lens: Use behavioural data to find where the value is

The foundation of personalisation is acting on behavioural data. The precursor is to avoid grouping customers (segmenting as this is NOT personalisation) look at each individual’s personal behaviours and needs. Many companies find it useful to start with segmenting behaviourally based segments as a first step in their evolution to 1:1 marketing. Respecting it was appropriate when you were at Uni, it has been overtaken now, get with the program.

The next task is to understand, for each segment, the customer journey – the series of interactions with a brand from initial consideration, to purchase and use, and then to subsequent purchases. Marketers can do this by integrating information from internal sources such as impressions – visits to the company website, purchases at a store, or calls to the contact centre, with information that can be acquired from external sources, such as prospects’ visits to a competitor’s website.

Combining this information and customer journeys creates a big-data requirement, which form the basis of 1:1 personalisation. The potential of all this information must be evaluated and prioritised carefully, based on relative value. For example, a leading retailer we worked with determined that it is more valuable to engage its customers within their “resupply” window—e.g., by reminding them they may be running out of toothpaste and their favorite brand has a limited-time offer—than by pushing them to go deeper in the category by suggesting other oral-care products such as mouthwash or teeth whiteners. But each individual is unique and treating them so is the holy grail. 

Listen and respond: Plan in advance to react quickly to customer signals

Personalised marketing is a two-way street: The customer provides signals—information about his or her needs and intentions—through activities like purchases, online browsing, and social media posts. The company identifies the opportunity and either responds to the signal with a relevant and timely message,  called trigger marketing, that is sent to the individual customer. However predictive personalisation achieves 20x higher returns.

Personalised product selection solutions (PPS) , using predictive analytics technologies, such as SwiftERM, identify consumer’s future behaviour ranking every SKU by greatest likelihood of that individual consumer to purchase from all the SKUs you have listed, in order of greatest likely buying propensity.

In other words, the ones they love best. It presents them to that individual at exactly the right moment, thereby maximising that individual’s customer lifetime value CLV potential. (i.e. Likelihood to Purchase, Discount Affinity, Likelihood to Churn etc). Hardly surprising is ranked at the top of all marketing disciplines for ROI.

Marketers often view personalisation at scale as a daunting undertaking, requiring millions in IT investments. But successful players often start small, generate top-line impact quickly—in a matter of weeks, often—and self-fund the initiative after that. Only then can you invest in the automation and institutionalisation of new ways of working across the whole organisation over time.

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