Marketing and sales teams are increasingly using predictive intelligence to uncover insights into their customers and prospects from the data generated by their campaigns, captured by their marketing technology stack and created by their prospects across the broader B2B web.
The next challenge is identifying bottlenecks in the lead-to-revenue process where predictive intelligence and data-driven decision making can make the greatest positive impact. After rolling out predictive intelligence across dozens of marketing and sales organizations in enterprise and mid-market companies, the 6sense customer success team has focused on four business use cases they’ve seen drive the most dramatic results.
In the first blog of a two-part series, we spotlight the business processes and implementation guidelines for the two marketing use cases of predictive intelligence.
Account-Based Digital Advertising
In our age of revenue-marketing and pipeline fixation, digital advertising is sometimes left to play second fiddle, as demand generation and sales campaigns hold the attention of marketing leaders and business executives. This is an odd state of affairs as digital budgets at most organizations continue to dwarf spends focused on down-funnel activities.
The reason so much attention is focused on down-funnel demand-gen activities is that, until recently, it has been impossible to gain real visibility or control over your media spend. As the old adage went, CMOs have been wasting half of their digital advertising budget, they just didn’t know which half.
6sense, working with our media and data partners, has taken on the challenge of delivering visibility into the opaque world of media. We have proven that predictive intelligence can have an outsized impact on how companies work with their digital advertising partners and how those ads reach and convert prospects and customers.
Business Challenge:
Lack of visibility into accounts reached by digital advertising.
Waste of media budget when ads are served to the wrong accounts or the wrong message is served to the right accounts.
Minuscule inbound conversion rates from advertising campaigns.
Goals of Implementation:
Ensure that your media budget reaches accounts in active buying cycles for your products and solutions.
Deliver messaging that is product and buying-stage relevant.
Validate the accounts reached through publishers and ad-networks.
Improve conversion metrics and program efficiencies.
Use Case:
To reach the C-level audience Dell knows they need to influence, their marketing team invests significant resources and budget on their relationship with Forbes. The long-standing partnership allows Dell to engage with key decision makers in their deals, but historically there have been some limitations. Dell has been unable to identify exactly the accounts it reaches through Forbes and as an extension, could not serve personalized messaging or ingest engagement data from their campaigns back into their systems.
To improve targeting, customize messaging and bring that data back into the Dell system, Forbes and 6sense worked together to cookie the Forbes digital ecosystem. This gave 6sense and Dell visibility into which accounts they were reaching on Forbes. 6sense then provided Dell with a list of accounts that were in active buying cycles for Dell products, thus allowing Dell to only target those accounts on Forbes. Furthermore, Dell was able to serve product-specific and buying stage-specific messaging to these accounts.
The results were: an optimized spend focused on accounts in an active buying cycle; better targeting that allowed Dell to deliver a relevant message through the best Forbes solution; and, and improved experience for Dell’s customers and prospects. These results can also be delivered across media partners and other digital platforms.
Account-Based Lead Generation
Lead generation has risen to become one of the single biggest contributors to business growth in B2B marketing. Demand generation managers are some of the most sought after professionals and the ability to manage a lead-to-revenue pipeline is perhaps the most prized skill set.
Still, significant challenges continue to plague demand gen marketing. Marketing and sales teams struggle with poor lead quality, which leads to low lead-to-MQL and MQL-to-SQL conversion rates. For larger organizations, the fact of buying the same lead over and over again has become an accepted cost of doing business.
What if organizations could identify gaps in their lead databases and only purchase leads from accounts they saw to be in active buying cycles and from which they lacked key decision-makers and influencers?
Business Challenge:
Poor lead quality.
Low lead-to-MQL and MQL-to-SQL conversions from:
Content syndication programs
Qualified lead generation programs.
Wasted budget spent on purchasing duplicate leads.
Goals of Implementation:
Improve budget allocation to focus on the purchase and engagement of leads from accounts in active buying cycles.
Increase conversion rates and lead velocity to accelerate the sales cycle.
Save resources by avoiding costly qualification processes for cold leads and building pipeline by reaching out to the right leads sooner.
Use Case:
Working through account-based lead generation partners, marketing teams can now run targeted programs aimed at capturing leads not only by demographic and firmographic fit, but also by targeting accounts in active buying cycles for specific products. Using predictive intelligence to build outbound lists, demand generation managers can target accounts based on the products they show interest for and where they are in the buying cycle.
This extra level of intelligence allows marketing teams to route leads that are closer to the point of sale through tele-qualification processes or directly to an account executive. Simultaneously, leads that have just entered a buying cycle can be served relevant thought leadership and education content. The goal is two-fold: decreasing wasteful spending by routing the right leads to the right follow-up and increasing conversion by providing a more customized experience.
Look out for our next post where we’ll cover the predictive intelligence use cases for B2B sales! In the meantime check out our webinar on the Use Cases of Predictive Intelligence.