Today ’s post is by Limor Wainstein, a technical writer and editor at Agile SEO, a boutique digital marketing agency focused on technology and SaaS markets. She has over 10 years’ experience writing technical articles and documentation for various audiences, including technical on-site content, software documentation, and dev guides. She specializes in big data analytics, computer/network security, middleware, software development, and APIs.
Although sales forecasts, email open rates, profit margins, and IP resolution data are all part of the sales numbers game, they’re single data points that give only a sliver of information. Data-driven sales has evolved to include a much more integrative look at the components that tell a sales story – from both a detailed and whole-picture view.
With the right data serving as the foundation of sales enablement, organizations can determine which content, tools, and techniques will best serve their sales team – from lead gathering and initial contact to closing deals and cross-selling.
Here are some of the most innovative ways organizations are evolving in their use of data-driven sales.
#1: Choosing data insights that feed sales enablement
Although basic data collection will always be important, it provides only the bare bones of value to an organization’s sales team. Social media analytics may help you determine what prospects are saying about your brand, but which industry influencers are affecting these opinions? Knowing who’s visiting your Website is good, but understanding if and why they have the potential to become star customers is better. Likewise, knowing which sales reps have the best closing rates is crucial, but knowing where the other sales reps are losing prospects in the sales funnel is even more helpful.
Don’t know what you don’t know? Check out this list of 14 data analytics from Boundless Markets that could provide insight to your sales enablement.
#2: Shifting how organizations use data
Where once top companies used data analytics to simply collect information and maybe apply it to production, now it’s being used to provide both insight and strategy.
IBM’s blog breaks this down to an evolution from “data-guided” to “data-savvy” – and, finally, “data-driven.” The first transition (from “data-guided” to “data-savvy”) often occurs after the organization has tried a variety of tools and vendors and finally realizes they’ve been spending money but not making tons of progress with the use of their data.
The “data-savvy” phase provides great insights into failures and successes, but the shift to being a “data-driven” company happens only when the organization is ready to use the information to create strategy. Sales enablement is fully supported.
#3: Improving sales enablement tools
Arming sales reps with state-of-the-art sales enablement tools may initially lead organizations to assume they’ll be looking at budget-busting technologies. But the truth is two-fold: Some of the best sales enablement solutions aren’t that expensive – and, when implemented properly, they’ll quickly pay for themselves.
Here’s a small sampling of sales enablement tools that can help take the guesswork out of what data to farm, what it means, and what to do with it:
- Crazy Egg uses heatmap technology that tells you where users came from, what they want, and how they behave on your site – including how far they scroll.
- IdeaScale puts the power of crowdsourcing to work via feedback and solution-based ideas. Among other features, organizations can customize imagery, language, and architecture for specific communities, and organize customer lifecycles into activities and goals.
- Pipeliner gives organizations a visual of their sales teams in real time to provide insight from five views: ranked, weighted, unweighted, balanced, and real.
- Hoopla uses video, data analytics, and game mechanics to turn sales goals into contests. Organizations can motivate sales reps with leaderboards, track sales, and show milestone completions in real time.
#4: Incorporating predictive intelligence
In the past, organizations had to rely on educated guesses, hunches, or general data to predict which products or services prospects would buy, how much they’d buy, and when. The development of predictive intelligence technologies has changed the game for sales by prioritizing leads, helping marketing teams create and deliver relevant ads at each stage of the buying cycle, and producing account-based campaigns aimed at specific targets.
With tools like predictive scoring, organizations can use data science to identify potential customers. Marketing teams can make real-time adjustments to their campaigns and pick the best leads for their sales team.
#5: Onboarding and training new employees
Keeping up with the evolution of data-driven sales goes beyond just sales engagement programs that help prospects and customers.
Organizations can upgrade to intranet software that helps sales reps engage and collaborate with their team members, share content and training materials for new reps who are onboarding or continuing sales training, and track progress.
These pieces need to be integrative (e.g., with customer relationship management), adaptive (e.g., with mobile and tablet capabilities for sales reps who travel), and multisensory (e.g., video, documents, audio) to be most effective.
If your organization is looking to master the way it uses data to improve sales, it may be time to change things up. These tools and approaches can escort you into the future of data-driven sales success.