Bluffing Your Way Through Dreamforce – Predictive Analytics

September 29, 2016 Ari Soffer

If you use Salesforce, your inbox is probably filling up with invitations to all kinds of Dreamforce martech vendors’ parties. But if you can squeeze in some time before lining up for U2, it’s also a good place to learn more about B2B marketing tools, tactics and best practices.

Between the planned launch of Salesforce Einstein and the presence of predictive analytics vendors providing demand generation solutions for the Salesforce ecosystem (including Leadspace), there should be lots of talk about predictive, artificial intelligence, semantic understanding and plenty of other marketing buzzwords (what a mouthful – I’m excited already!).

Don’t worry. We’re here to help.

Predictive analytics will come up during Dreamforce

There’s no doubt about it. Predictive analytics is rapidly gaining popularity – and curiosity – among B2B lead generation professionals. It’s bound to feature at Dreamforce 2016.

So, if you get stuck in line at an open bar and the marketer next to you starts bragging about how she increased lead conversion with predictive analytics, here’s what you need to know to join the conversation.

First, the basics. Predictive analytics uses machine learning to understand which leads are most likely to buy, making for a far more efficient sales funnel.

More advanced predictive models combine artificial intelligence with the human kind, allowing your sales and marketing teams to adjust the predictive model as necessary. This is a crucial advantage in a predictive platform, because when all’s said and done, nothing beats human know-how and experience.

Prioritize the right leads

So what advantages does all this offer to your business (assuming you know what you’re looking for)?

Predictive analytics essentially brings together all the disparate – often unused – data and intelligence hidden within your CRM and marketing automation systems to form a highly actionable model.

By analyzing previous customer behavior and traits, an effective predictive platform will be able to create an Ideal Customer Profile (or “ICP” if you like abbreviations – which you do, or you wouldn’t be in B2B sales and marketing). Using that profile, you can score and rank your leads in order of which are most likely to convert, and prioritize them for your marketing, sales and SDR teams to deal with accordingly.

For example, leads ranked as having a high propensity to buy will be sent directly to your SDRs, while lower-ranking leads with potential can be diverted into a marketing nurture stream. The lowest-ranking leads can either be put aside completely or sent for more basic nurturing, depending on your capacity and the specificity of your campaign.

You could also use predictive analytics to create different Ideal Customer Profiles for numerous campaigns targeting different audiences.

The benefits here can’t be overstated. Your sales reps in particular will save countless time and resources chasing the wrong leads. Instead, all the right leads can be targeted appropriately, depending on where they fall within your sales funnel.

Ultimately, that means saving time and money, and generating more deals overall.

Expanding your horizons – and numbers of net-new leads

The same model can also be used to by Sales and Marketing to prospect for net-new leads in a far more precise way, targeting only the best potential prospects with the right kind of material.

For example, Leadspace customer BloomReach, an early adopter of account-based marketing (ABM), used predictive analytics to source 78% of their net-new leads.

ObservePoint, another Leadspace customer, achieved a 640% (!) ROI with predictive analytics. Their SDRs were able to identify 35% more leads with Leadspace Predictive Analytics, while also increasing their connection rates by 23% due to Leadspace’s integration into Salesforce.

In the same vein, predictive analytics is a great way to make sense of unfamiliar territory when breaking into new markets.

That’s what Leadspace customer RingCentral did. One of their objectives was to expand into their white space, but they were having trouble identifying the right leads. The precision of their predictive model “turned on the lights,” RingCentral Chief Marketing Technologist David Cowings recounted in a recent webinar.

“80% of the time Leadspace called something into a segment, it was falling right in line with what the sales reps had previous aligned that target with,” he said.

If you’re familiar with account-based marketing (ABM), you should already be leaping from your chair in B2B marketing-induced ecstasy. The precision, efficiency and focus on individuals provided by predictive analytics makes it perfect for guiding ABM campaigns.

So there you have it: everything you need to know to bluff your way through predictive analytics (and the open bar) at Dreamforce.

But if you really want to go deep – perhaps in hopes of leaping onto a podium and taking over – there’s plenty more where that came from:

  • Read Leadspace’s Predictive Power of Three ebook, to discover the 3 key elements in predictive analytics which drive superior results in demand and lead generation.
  • For more on how predictive scoring in particular works, click here.
  • And here’s a cute video squeezing everything we possibly could about Leadspace’s predictive analytics platform into one minute.

If you’re still bursting with questions about predictive analytics, you can catch us at Dreamforce 2016. Just don’t bother us at the open bar (only kidding.)

Image credit: iStock

The post Bluffing Your Way Through Dreamforce – Predictive Analytics appeared first on Leadspace.

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