How To Answer The 5 W’s of B2B Marketing With Predictive Analytics

December 19, 2014 Blake Brysha

Marketers are drowning in data. Across any number of platforms (Salesforce, Marketo, Google Analytics, etc.) we track everything and, as a result, we amass more records than most can effectively manage and interpret. We know that if analyzed correctly, this data contains powerful insights, but too often analysis leaves CMOs and their teams with more questions than answers.

Today, smart marketers are replacing pivot tables and manual analysis with technology to automate the process and help them identify what’s working, intelligently plan and forecast, and draw a direct correlation between marketing activity and revenue. In doing so, they’re able to take control of marketing, transforming it into a true revenue function.

The ubiquity and availability of data has brought us into a new era of data-driven marketing—allowing us to finally answer the most challenging questions in marketing. The following are the five key questions that predictive B2B analytics can help address:

Who: Target Audience

As marketers, we must cater to any number of audiences throughout the sales cycle. B2B purchase decisions often require the input of many stakeholders and an intimate familiarity with the characteristics of these target influencers is critical. Using data-driven insights, it’s now possible to identify which profiles are most vital to a sale. Blending traditional demographics with behavioral patterns—how prospects interact with both native and external touchpoints—helps us develop precise profiles of those with the highest propensity to buy. With these insights, marketers can more effectively target marketing to ensure they’re mapping activity and messaging to the most receptive audience.

What: Campaigns and Themes

70% of B2B marketers are creating more content than they did just last year, but how much of this content is actually providing value to the prospect? How much of it is presenting a message that truly aligns to a target’s interests and pain points? Content and messaging are too often developed in silos, based chiefly on Marketing’s perception of which themes will resonate with an audience. Predictive analytics allows marketers to leave the guesswork behind and embrace data-driven messaging. By analyzing everyday activity captured in CRM and marketing automation systems we can gain strategic insights that can be applied to the more granular elements of messaging—ideal theme, audience, product, region, and which cohorts work most effectively together. Predictive analytics helps automate this process, tagging themes and associated cohorts to tie messaging directly to sales.

Where: Which Channels

B2B Marketers use an average of 15 different channels in demand generation activities. For many, this number can far, far higher. Prospects engage with your brand across so many touch points—online and off—and it’s imperative that B2B marketers understand the role that each of these channels play in the evaluation process. While a webinar found through LinkedIn may be the final push to move an opportunity to sale, it’s irresponsible to discount prior campaigns and channels that also helped move the needle.

Most marketers still rely on single-touch attribution models—crediting a sale to only the first or last touch—but multi-touch attribution is necessary for full visibility into channel efficacy. With proper crediting of all channels involved in the path to sale, marketers can accurately model and measure the buyers’ journey taken by prospects, and tailor investments accordingly.

When: Targeting and Velocity

The B2B buyer’s journey is complex, spanning numerous stakeholders across any range of touchpoints, and Marketing now owns 75% of the sales cycle. With predictive analytics, marketers gain visibility into where targets will be most receptive to various schools of messaging along the path to purchase. Do eBooks work well as a first touch asset? Where in my nurturing track should I introduce case studies? After how many touches should Sales contact a lead? Specific content offers are more relevant to specific stages of the buyers’ journey and identifying the “when” is key to providing value to prospects.

Furthermore, by tracking progress along the complete revenue waterfall, predictive analytics can help marketers get a grip on velocity. Where are leads falling off or slowing down? Which efforts produce the shortest velocity results? When can I expect an investment to translate to revenue? With visibility into velocity patterns, B2B marketers can accurately forecast future revenue impact and align their plans to company goals.

Why: Data-backed insights facilitate confident bets

Arguably the most important of the set, understanding why something is or isn’t working is critical to making the big decisions that can transform marketing. Being able to answer why an activity was successful (i.e. the specific intersection of who, what, where, and when), builds respect, accountability, and helps secure/protect budget. The same is true for planning and forecasting. By understanding why certain programming has worked in the past, marketers can now predict precisely when and how much revenue will be produced as a result of their efforts. Predictive analytics helps facilitate smarter bets and justify there investments with the ability to accurately predict why/when an investment will turn into revenue.

Bonus: The “How”

Of course, we’d be remiss in not mentioning the red-headed stepchild of the group, the “how.” The past year has seen the rise of “analytics cloud” solutions promising to be everything to everybody—one-stop shops for organization-wide analytics. The reality is: most of these technologies aren’t built with marketing in mind, and traditional BI tools fall short when it comes to the unique needs of marketers. Marketing needs its own analytics and thankfully, the tools exist to help gain complete visibility into marketing’s impact on sales.

Predictive analytics solutions are facilitating data-driven marketing operations for companies of all sizes. Rather than adding headcount for manual analysis, smart B2B CMOs have embraced technology that’s helping them take control of marketing, tie efforts directly to revenue, and answer the big questions with the power to make or break a company. Data-driven marketing has arrived and the pioneers who are already using predictive technology are being met with significant competitive advantage. In the age of data-driven marketing, only one question remains: will your organization embrace predictive analytics… or risk being left in the dust?

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