Why What You “Can’t See” Will Outweigh What You Can: Interview with Kerry Cunningham of SiriusDecisions

 In B2B Marketing, Predictive Intelligence

Kerry Cunningham, Research Director at SiriusDecisions, has more than 20 years of experience in b-to-b demand creation and management, spanning a broad array of industries and markets.

6s: What do we need to understand about the buyer’s journey today?

KC: The buyer’s journey doesn’t look like what our marketing platforms and lead nurturing portray. They portray the journey as linear, but it’s really not. It may involve online and offline at the same time. It may move back and forth between the two, or the two may be occurring at exactly the same time. The journey is going to be happening in ways that you can see. But also in lots and lots of ways that you can’t see. You have to assume that the ones that you can’t see will outweigh the ones that you can…substantially. So the idea of having lots of data to characterize your prospects, and to characterize their buyer’s journey, is really critical.

We saw that the buyer’s journey varies according to the complexity of the solution being sold and a number of different variables. Whatever your buyer’s journey is, you have to understand it from the perspective of the buyer and not from the perspective of what works well now with the current systems that you have.

6s: When you talk about the things we can’t see, what things are you talking about?  How are we still in the dark?

KC: The prospects in our marketing automation platform. We can see who they are because they have identified themselves. We can see what they have done with us. There are also an awful lot of prospects that haven’t identified themselves. All those prospects, whether they have identified themselves or not, are continuing to educate themselves and continue their buyer’s journey elsewhere in the world, outside your digital realm.

6s: Changing gears… You have said that companies you are working with are excited about the promise of predictive… What advice are you giving to companies who are implementing this technology now?

KC: The first thing to note is that right now we have really ineffective lead scoring solutions where leads are being sent to sales and teleprospecting, and they are not working well in either place. For most organizations, before putting in a model and starting to deliver leads that are much, much better to sales, we need to test and educate.

We need to have processes in place to understand: how much better are the leads with predictive, in what way are they better, and how are we going to communicate that they are better so sales believes that they’re better. Then we need SLAs to make sure that the leads get contacted. If you produce great leads, and you give them to a sales team that is used to cherry picking, they will cherry pick.

If you are producing net-new leads, prospects that you have never talked to before but are showing signals from elsewhere in the world that they are in a buying process, one of things you still have to manage is that for sales reps, that’s still a cold call. So if communications with sales aren’t clear, that this prospect is not expecting your call and that they don’t know you yet, then the sales rep will be disappointed when they pick up the phone and the prospect doesn’t say, “Oh gosh, I am in a buying process for the solution you sell.”

So that piece of the process is really, really critical. A sales rep will do extraordinarily well with new leads when they know what they are. And if they can get to know the “why” behind the predictive score by using the output from the predictive solution to build and drive some of the enablement.

6s: What can we do to get everyone used to this new paradigm?

KC: If the model is producing something that is unexpected, what’s different about it? Is it different in a way that we need to train sales? A great thing to do is to run a test so you have a benchmark against your existing systems. This way you can set appropriate expectations and develop champions that can help you communicate about how to use the output.

As I said earlier, one of my cautions is that people get really excited about the promise of predictive. When sales people get excited, and are under the pressure to produce, they are going to treat you as if you are withholding life-saving drugs from their grandmother. It’s difficult to be disciplined enough to run your tests and see how this is going to work before you roll it out to the entire organization. But it’s critical to do it.

6s: Tony Jaros said that “incentive compensation is the third rail in marketing, product [management], and sales alignment”at #SDSummit. How does changing the way teams are incentivized contribute to organizational alignment?

KC: Tony’s recommendation is to make sure that your company is completely aligned to what the real organizational goals are rather than having them be incentivized by “on-the-way-to…” They should be incentivized by goals that produce ultimate outcomes, revenue, pipeline…or as close as you can get to that. When everyone is aligned in the same direction, the operation thinks about solving problems in same way. It’s really critical to understand the ultimate outcomes and ensure that incentives are aligned with those.

When you talk about lead generation and demand generation, if people have goals and are paid to produce something that has an uncertain relationship with the outcome of the business, then they can be receiving their full compensation and incentives without actually contributing to what the business really needs to accomplish. There is always the tension of time between the effort to do the work and the ultimate outcome. In economics, it’s the idea of future fis-counting: the further out in advance my payment is, the less I value it. If your sales cycle is nine months long, and I have to wait to get paid for the thing that I did nine months ago, it’s not going to help me much. Incentive has to be as close as possible to the thing that aligns to the business and what you’ve produced.

Where things like predictive technologies can help is the ability to get much closer to when a lead is produced, delivered to sales and closed. Then I know what I am producing further back in the pipeline and my activities are more aligned to the outcome that the business needs.

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