This is the third post in our profile management blog series. Earlier this month, we talked about whether profile management requires predictive scoring, and in this post we’ll discuss how it can be easily incorporated into your existing sales and marketing workflows. Often we talk with companies that don’t yet have enough leads or conversions to build a statistically accurate predictive model, but that no longer needs to hold them back. The key to establishing impactful data-driven workflows – with our without predictive scores – is creating actionable profiles of your ideal customers, and infusing that insight into your day-to-day work.
For example, say your ideal profile is “Early Tech Adopters.” This profile is of course a summary of many different criteria, such as companies that use technologies like marketing automation, advanced web analytics, or mobile tracking; within certain annual revenue bands or even geographies. Could you develop a target segment in Salesforce? Yes, but it’s pretty painful, because you’d have to buy lists from a ton of different data sources, import those contacts or accounts into Salesforce, combine the external signals with data you already have sitting in your CRM or marketing automation, and then set up advanced formula fields. Even a talented Salesforce admin would need weeks to build a single profile.
Descriptive, Data-Rich Profiles in Minutes
Infer Profile Management, on the other hand, can help you automate this tedious workflow. You simply choose from a wide range of attributes – i.e. basic signals like contact title, company size or geography, or more complex characteristics such as a person’s recent marketing activity, their company’s overall fit for a product, or their current state within the customer lifecycle – to create any profile your sales and marketing teams want to target.
Once built, you can publish profile tags directly into your CRM, or share them across marketing systems like Marketo and Eloqua. Moving forward, Infer will automatically identify and tag any new inquiry that matches your profile criteria. Best of all, Infer’s profile tags only take up one slot in your Salesforce record, unlike many data append or enrichment tools that need multiple rows. Each of these fields must then be mapped, which can become quite onerous.
Getting the Most from Your Data Investments
It’s great in theory to invest in lots of data sources and applications that collect customer data, but they add no value unless your teams actually adopt them and leverage the insight they bring as part of their daily workflows. With Infer Profile Management, you can finally bring together all of the data you’re investing in, and build profiles over it.
This comes in handy with common scenarios like using Google Analytics to monitor your Web site traffic, which is can be very helpful. However, a downside is that neither Salesforce or Marketo can create a lead out of an anonymous site visitor. Those systems don’t capture anything until the visitor becomes known, probably by filling in a form on your website. Google Analytics, however, is tracking both known and unknown visitors in the background. Using the Infer platform, you can fuse all of that data to contacts in Salesforce once they identify themselves (and the timing of when they do that doesn’t matter as long as the cookie stays intact). As a result, you can now build an Infer Profile over behavior data from both systems — i.e. a list of people who “spent more than 5-min on my website” or “visited the pricing page” (or any specific URL that your business might be focusing on).
Profiles in Action
With these Infer Profiles, you can instantly tag everyone in your database that exhibits similar behavior and have your marketing team and sales reps run programs around that. This also allows you to better personalize outreach by sending specific segments relevant, high-value content (and avoid sending something they’ve already seen or read). We’ll be sharing more specific workflow examples in the next post of this profile management series, so stay tuned.