By Matt Pigott - February 14th, 2017

Last in a four-part series on personalization in 2017

Time it to perfection

Much is spoken of in terms of going granular, but in order to cut through the general noise and reach the individual customer with a meaningful question or message, it helps to first understand the general circles and cycles they move in. Much can be gleaned from customer attributes such as age, gender, ethnicity and geographic location, but even more insight can be gained from understanding their personal choices, the times of day they like to browse or shop, which colours they prefer, what their average purchase price is, etc.

The longer this sort of information is gathered for, the more brands will understand what makes their customers tick and what they are most likely to buy again, or what services or products, based on a points system, they are likely to be most receptive to. But the timing of any interaction is also key.

For example, the likelihood of somebody being receptive to the suggestion of buying a pump and helmet after they have bought a bicycle will be far higher than a random suggestion to buy a pump and helmet before the higher ticket item has been purchased. Unless the real-time information showed that the customer was browsing bicycles. But then, the pump and helmet suggestion would be out of sync with the customer’s buying cycle, and as such way off key, creepy...intrusive. Nobody wants to feel that they’re being spied upon, which is why sensitive timing is integral to delivering good personalization. In short, there’s preemptive, there’s predictive (or the semblance of it), and there’s plain presumptive. The latter might work, but it’s a dangerous game to play.

First names - keeping it simple and a final word on personalization

It’s worth noting that, according to research conducted by Experian, even an email with a personalized subject line enjoys a 29% increase in open rates and a 41% uptick in unique click-through rates. This demonstrates the simple revenue-driving power of a first name. And yet, astonishingly, more than half of companies that use email in their marketing communications fail to personalize their campaigns at this most basic of levels. All too often, it’s because the data needs cleaning, which is usually a mammoth task. But anything that improves a company’s bottom line must be worth it.

For marketers that want to see an increase in the fiscal outcomes of their campaigns, as dull as it sounds, going back to basics first, cleansing databases so that names and other obvious details are correct, and bringing siloed cross departmental data into the same systems before thinking about higher end drivers such as data science and how it intersects with marketing strategy, might be worth doing.  Because clean data will ultimately provide the springboard that propels brands to the higher reaches of algorithmically driven real-time interactions and predictive analysis, and will help take a company struggling to gain traction with its customer base toward a new level of meaningful interaction.


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