As a marketer, you’ve heard the legend of marketing automation. The tale goes that there’s software out there that can move prospects along the buyer’s journey, delivering highly personalized experiences, all with minimal effort from marketers. The story is a promising one, and one that many marketers have already invested substantial time and budget in, but it’s an incomplete one. Despite mass adoption, 85% of marketers don’t feel that they’re using automation to its full potential today (according to Sirius Decisions).
The name marketing automation is, in itself, a bit of a misnomer. The word “automation” conjures up images of a solution that will robotically and effortlessly attract leads, nurture them, and surface the best prospects for Sales. In theory, marketing automation can do this, but only with a considerable amount of manual effort. This often requires a dedicated automation engineer or professional services agreement with the solution provider—both costly options and not at all automated in the true sense of the word.
Lead scoring—a core tenet of marketing automation—helps Sales and Marketing determine which leads are most qualified, the best ways to engage with them, and understand when they are ready to talk to sales. For established companies with a steady flow of inbound traffic and leads, a lead scoring system is absolutely necessary. Lead scoring, as you might have guessed, also requires a lot of implementation time to get right. I’ve personally built quite a few lead scoring models in my career and I will attest that each one took countless hours just to implement initially. Add to this the ongoing fine-tuning required to keep the scoring model in sync with business goals, the regular adjustments to campaigns and content, and the inevitable calls to customer support. The time required to keep automation running is substantial. But does it need to be this way?
I believe that the future of automation is, in fact, automation. Leading marketers will take advantage of big data and predictive technologies to turn today’s manual, fairly static automation processes into dynamic, ever-evolving systems able to adjust marketing activity in real-time. Using predictive algorithms and tapping into the wealth of prospect data available (behavioral and demographic; native and public), automation systems will be able to instinctively build and adjust lead scoring, routing rules, identify the next best marketing campaign to run, and tell marketers exactly where to invest their hard-fought budget.
Most organizations are not quite there yet, but that doesn’t mean automation isn’t still powerful. It is, and the companies equipped to spend the time and resources required for proper automation maintenance are reaping the benefits. Although, the truly innovative companies are supplementing these efforts with predictive technologies, able to look beyond traditional lead scoring rules, determine the characteristics of a good lead or account, and what it will take to convert them—resulting in huge gains in efficiency and sales.
Thus one can wonder, where is the automation in marketing automation? Until automation can live up to the hype implied in its name, companies that seek truly automated marketing should always have predictive on the very same shortlist of must-have martech.