Customer acquisition: target the best, come back for the restBy Jon Taylor on November 21, 2017
US merchant John Wanamaker is considered by some to have been something of a marketing pioneer and is credited with the phrase: “Half the money I spend on advertising is wasted; the trouble is I don't know which half.”
Given that Wanamaker died in 1922, we can surmise that return on investment (ROI) is not a new bone of contention for marketers.
We know from experience that marketing and advertising spend is still a concern for many businesses today, particularly at a time in which results are expected to be increasingly transparent. Fortunately, nowadays, marketers have ever more sophisticated tools at their disposal, rather than having to just rely on advertising.
One alternative is to use data, which, as you might imagine, is something we’re rather au fait with. The customer acquisition service we offer at Peak isn’t based on speaking to the largest number of people, but on identifying the prospects that are most likely to become customers. You don’t need to be a marketing pioneer to see how this approach can reduce the cost per acquisition for organisations and their overall marketing ROI as a result.
Although our approach relies upon sophisticated technology and the accomplished expertise of our data science guys, it is, in essence, very logical and straightforward. By bringing together data like customer history, behaviour, purchases, preferences and social media activity, and then using algorithms to cluster and classify similar groups of customers, we can attach a probability of conversion to each new lead based on the group they call into.
This not only allows organisations to focus their efforts on converting the prospects who are most likely to become customers, but to tailor their service to appeal to those prospects too. In this way, organisations can be confident that they are acquiring customers at the optimal cost.
To get an idea of this in practice, you can take a look at how we worked with music streaming service Leaf. Using the platform’s data, we were able to identify its most valuable users, how they were acquired and how they used the service. Leaf was then able to use that information to better target its marketing activities and shape its platform going forward, ultimately doubling its number of active users to 1.5 million over the course of four months. We’re pretty sure John Wanamaker would have approved.