With the rising adoption of machine learning and automation, a human touch becomes more important than ever. Companies that have figured out how to utilize data to create deeper personalization are not only improving the overall customer experience by talking in a language customers appreciate; they’re also winning more deals and generating more revenue dollars.
So why aren’t more businesses taking this approach?
The unfortunate truth is that too many marketing and sales teams are lost in the weeds, trying to navigate a fragmented technology landscape with thin or noisy data. Marketing may keep information about website clicks in Marketo, while sales development reps track their own set of prospect activity in separate tools like Outreach or Tout.
Overwhelmed by the complexity of disparate systems, employees will too often ignore critical components of customer data altogether. With a lack of understanding or alignment about what makes a prospect a good fit to buy their company’s product, many teams still employ dubious “spray and pray” tactics.
This is true of startups that are just hitting their stride, or even large companies that are awash with inbound inquiries. This “volume over quality” approach wastes resources, produces lackluster results and can be damaging to the brand.
It’s time for B2B marketers to take note of a sophisticated marketing approach that’s been driving results in the B2C space for quite some time: processing large amounts of data into actionable intelligence.
Google, with its Now offering, is a great example of a B2C company that leverages consumer data from a plethora of sources (e.g., what you search, what types of emails you’re receiving, calendar invites) to make crazy-accurate, highly personalized recommendations for users — from what articles one should read to the weather report for an upcoming trip to another city.
Fortunately, new developments in B2B marketing technology are enabling companies to unearth deeper customer signals from external sources like patent filings, job listings or social media and consolidate them along with information from internal sources like a CRM (customer relationship management) system.
All of these signals can be aggregated into a data-rich profile of each prospect or customer, which can in turn be sliced and diced — or hyper-segmented — in countless ways.
Supercharge Program Performance With Best Practices
Without a strategic plan of attack, your top prospects risk remaining just another name on a list, or worse, a competitor’s newest customer. But with hyper-segmentation, you can leverage all of your buyer signals to get more granular.
For example, a profile may include a wealth of buyer signals such as native marketing automation lead scoring, account and behavior scores, predictive scoring models, a matching persona and “technographic” traits, like what applications and platforms the company is currently using.
Being able to then drill down to narrow, but fluid, segments allows marketing and sales to increase the efficacy of their lead nurturing in high-performing territories or in accounts that are more likely to close faster.
Furthermore, it allows them to laser-focus their account-based marketing (ABM) strategy on a well-defined, prioritized list of the most qualified accounts.
Prioritize Segments And Personalize Outreach
Both prioritization and personalization are key when it comes to your hyper-segmentation strategy. Rather than creating a few rigid personas or a large list based on broad firmographic characteristics, hyper-segmentation allows you to use all of your customer data to pinpoint specific marketing problems you can solve for smaller customer groups, aka a “segment of one.”
In order to align your efforts to impact, you must first figure out which segmentation parameters produce groups with the highest revenue potential, and then prioritize your marketing and sales horsepower behind those. For example, New Relic (Disclosure: client), a SaaS-based (Software as a Service-based) software analytics company, employs this method to prioritize high-velocity opportunities that have the potential to close more quickly.
With a highly segmented profile, you can speak to each prospect as an individual through the lens of their firmographics, persona, technographics and so on. For example, prior to initial outreach, you can arm your sales reps with valuable insight into each prospect — e.g., they are a B2B executive with recent hiring activity for cloud infrastructure positions, using Mixpanel (Disclosure: client).
This insight allows them to pre-plan personalized conversation points, tailoring a unique message that communicates a clear value proposition. Reps can have more meaningful conversations with highly qualified prospects who have a clear pain point their product can solve.
With less time spent on research and more time to craft their pitch, reps can double down on the best customer profiles.
Expand Into New Markets
Once you’ve experienced success in prioritizing the right segments, you can start expanding your marketable universe and determine where to go next. B2C companies often leverage predictive recommendations to suggest what content a consumer might want to consume next (e.g., on Spotify or Netflix), while in the B2B world, predictive technologies can use your data to “learn” which new product to offer a particular prospect or the next best market to enter.
For example, a product marketer looking to identify new markets may capitalize on what they have already learned from their hyper-segmented data and from predictive simulations of pipeline metrics: for example, which segments have the highest conversion rates, average deal sizes and sales cycle velocity.
Having information about other technologies your top prospects are using can help you fine-tune your product and marketing strategies and know where to deploy your resources for the highest chance of success.
The biggest benefit of these types of techniques is that you’ll increase the likelihood of hitting your target and making a big impact on company growth. However, it’s not enough to just have the data in your hands; you need to break it down into actionable intelligence that is meaningful.
With this insight, you can relentlessly focus on seeking out the best buyers for your product, and then make the process programmatic across your sales and marketing team so you can scale. Hyper-segmentation builds confidence through statistical measurement, so you know you’re focusing on the right areas and reducing the likelihood of massive opportunity cost.
Comments