Predictive Marketing Blog

INTERVIEW: 100 Tips For Customer Acquisition! (Ok, So Not 100)

Last month, the Direct Marketing Association (DMA) held their 2016 Marketing Analytics Conference in Austin, TX where they brought together marketers and data scientists to connect and share strategies for improving contact points with customers.

After the event, Reach Analytics CEO Bruno Delahaye sat down with conference organizer Marni Edelhard, Director of Content at Momentum Events, and shared his tips on savvy customer acquisition.

Check out our recap of the chat below and listen to the full audio of the podcast, as Bruno offers Marni 100 tips, but agrees to limit it to 3 or 4.


DMA’s Marketing Analytics Conference

Interview with Bruno Delahaye, CEO of Reach Analytics


1. Automation is already replacing manual data science.

In B2C marketing, predictive analytics is growing more complex, making it increasingly difficult for data scientists to perform tasks manually or ‘long-hand.’ This is leading to improvements in machine learning and advanced automation.

Also, despite the hype, cloud computing opportunities are still underexploited by marketing. Data collection is growing alongside advanced modeling. With the cloud, there’s potentially limitless computing power for predictive computation, which adds to the speed of predictive analysis.

2. Develop a deep understanding of your customer and prospects.

Automated predictive modeling is helping marketers in multiple ways. First it gives them a better understanding of who their customers are, in terms of what makes customers unique. It helps them find prospects who look like existing customers – easier, faster and more cost efficiently. And it helps marketers to build messages that will resonate intimately with prospective customers.

3. Still a lot of room for improvement.

Instead of making assumptions about a customer profile, top marketers are using analytics more often to make decisions. Yet, we’re still in the early stages. According to the CMO Survey 2016, only about 35% of marketing projects are using analytics. This is up from 29% in 2015, but marketing dollars are still mostly spent without rigorously learning from prior investments. Marketing departments still frequently structure their approach by channel, instead of by customer profile. Usually mimicking team silos, such as the digital marketing team, the direct mail team, etc. Yet customers expect to experience the brand as a consistent whole across channels. Siloed campaigns lead to fragmented and awkward customer experiences.