We believe that anyone can learn to do predictive marketing with the right foundation. In our series, “Core Concepts of Predictive Marketing”, Acquia’s Chief Science Officer, Omer Artun shares excerpts from his book: “Predictive Marketing: Easy Ways Every Marketer Can Use Customer Analytics and Big Data.”
This series will be a guide to everything you need to know about relationship marketing and predictive analytics in marketing. Dive in to learn how to activate your customer data and tap into unlimited opportunity.
So far we’ve gone over many use cases and benefits of predictive marketing, and now it’s time to get starting. But you don’t have to do everything at once. Just get started. Choosing the wrong vendor or the wrong campaign is not as bad as waiting. Your competitors are already leveraging predictive marketing today and gaining a significant competitive advantage from their early experiments. Remember that many companies are seeing the lifetime value, retention and loyalty of their customers increase dramatically using predictive marketing techniques.
Here are three recommendations.
1. Get Started Small
With a couple of thousand dollars a month and a couple of weeks of integration work, you can begin solving your customer data problem and run your first marketing campaign. The best way to build a case for predictive marketing is to just get started. Given the large returns expected for this investment, you really cannot afford to wait. Ask yourself how you would feel if your competitors deployed this type of technology first. How would your customers feel if they are getting personalized treatment from your competitors first, but not from you? Also, ask yourself if there are other projects on your plate that can truly give you a higher return on investment.
2. Bring Customer Data in House but Outsource the Data Science
We strongly believe that it is not possible to become truly customer-centric without making customer data available to all customer-facing personnel in your organization, starting with you — the marketers. Therefore, we strongly recommend against outsourcing your customer database to a third-party provider such as a marketing service provider. It will be too difficult to access data when and how you want it and the customer insights will reside outside your organization. Bringing customer data in-house does not mean that you need to hire expensive data scientists or technology resources. Easy-to-use, online solutions are available that allow you to own and access your customer data at any time, but use outside vendors to create the advanced statistical models. Data scientists are in high demand and most marketers do not have the bandwidth and expertise to hire, provide direction and retain such analytical personnel. The best data scientists that truly make an impact are the ones that have business acumen, which are even harder to find. Data science is a good way to gain insights but it is hard to make the information available at every customer touchpoint without extensive IT projects. Therefore, start with the end in mind and find the most practical solution that gets you to making a difference in the way your customers interact with your brand.
3. Complement Your Existing Infrastructure with Predictive Marketing
You don’t have to rip and replace your existing infrastructure. You can certainly get started by complementing your existing infrastructure with robust data cleansing and predictive capabilities. Start small and expand your deployment over time. This could include embedding predictive capabilities into your different marketing channels, such as email, and perhaps replacing your existing specialized tools with a single campaign management platform to coordinate campaigns across all channels.
Now that you’ve got a baseline for how to start building a predictive marketing strategy, check out the other installments of our Core Concepts in Predictive Marketing series for the different machine learning models and applications that you can explore with your customer data.