Two Key Promises of Predictive Marketing

As a B2B marketer, imagine how much more effective your marketing efforts would be if you had the following insights:

• What if you could identify businesses that are likely to have a strong interest in your company's products or services before you market to those businesses?
• What if you could reliably identify which of your current prospects have a strong propensity to buy your company's products or services and thus are ready to have a meaningful conversation with one of your sales reps?

These are two of the most significant promises of predictive marketing solutions. During 2015, predictive marketing was one of the hot technologies in B2B marketing, and it appears that the demand for predictive marketing solutions is poised to grow rapidly. 

Last fall, Everstring published the results of a survey of marketers regarding the use of various marketing technologies. Twenty-five percent of the survey respondents said they were currently using some predictive tools, and another 47% said they were aware of predictive marketing and were investigating how to use it. Two studies by Forrester Consulting - available here and here - reported even higher usage rates of predictive marketing analytics among B2B companies.

Predictive marketing solutions have the potential to dramatically improve the productivity of B2B demand generation by enabling companies to target their marketing and sales activities more precisely. Predictive analytics can be used to address a wide range of business issues, but the two uses that are receiving most of the attention in the B2B marketing world are new prospect acquisition and prospect/lead scoring.

Most predictive marketing solutions employ the same basic approach for both of these use cases. They take data regarding your company's existing customers from your CRM and marketing automation systems and combine that information with external data about those customers - from around the web, social media, and other third-party data sources - to construct a customer data model that describes the attributes and behaviors of organizations that are likely to have a strong interest in your company's products or services.

When predictive marketing is used to identify new prospects, the solution provider will run your customer data model against its (the solution provider's) database of businesses. The result is a list of prospects that resemble - to a greater or lesser extent - your existing customers. The inference is that prospects that closely resemble your existing customers  are likely to be interested in your company's products or services. With this insight, you can target your marketing programs more precisely and use your marketing resources where they are more likely to be effective.

When predictive marketing is used for prospect/lead scoring, the solution provider applies your customer data model to the prospects already in your marketing database and generates a score for each prospect based on how closely the prospect resembles your existing customers. This enables you to qualify prospects or leads using much more data than is typically available in traditional lead scoring systems. In theory, therefore, a predictive marketing solution qualifies prospects and leads more accurately, and it can potentially identify buying signals that are almost impossible to find using traditional lead scoring techniques.

The early indications are that predictive marketing solutions will drive significant business benefits. For example, in a 2015 study by Forrester Consulting, 72% of respondents whose companies were using predictive marketing grew revenues by 10% or more during 2014. Only 33% of non-users achieved the same rate of revenue growth.

While its clear that predictive marketing solutions can provide significant benefits in the right circumstances, there are a few caveats that marketers should keep in mind. For example:

• These solutions rely heavily on data from a company's CRM and marketing automation systems to construct the customer data model. So, if your company is a fairly mature user of CRM and marketing automation, and if your systems contain a significant amount of usable data, predictive marketing could be a sound investment. On the other hand, if you don't have enough reliable CRM/marketing automation data to work with, the value of predictive marketing will be more problematic.
• It's also important to recognize that you need a reasonable number of existing customers to create a customer data model that is reliable and predictive. Put simply, your customer data model will be richer and more reliable if it is based on 500 customers rather than on 50 customers.
• Predictive marketing solutions are not outrageously expensive, but they can require a significant investment. The cost of predictive marketing solutions varies greatly depending on the features of the solution and a variety of other factors. Pricing can always change, of course, but at present, it appears that the starting price for most predictive marketing solutions ranges from around $15,000 per year to over $100,000 per year.

Illustration courtesy of Louise McLaren via Flickr CC.