This co-authored byline was originally published on CMSWire by Sean Zinsmeister, Vice President of Product Marketing at Infer, and Adrian Chang, Director of Customer Marketing at Oracle Marketing Cloud.
Business-to-business (B2B) sales and marketing are entirely different from business-to-consumer (B2C) tactics — or that’s the general assumption.
One is relatively low volume and high budget, with lengthy, consultative selling processes and lots of personal relationships at play, while the other usually means huge volumes and low price points, with fast, direct sales processes.
B2C relies on consumers, transaction events, impulse buys and coupons. B2B is all about prospects, “journeys” and reaching people through content in context.
But more and more, we’re seeing these two universes converge.
Although we often perceive B2B companies as one step behind their B2C counterparts when it comes to adopting the latest sales, marketing and advertising techniques, that is quickly changing. B2C marketers have naturally excelled at bringing as many people as possible into the top of the funnel, but B2B companies have perfected the use of intelligence and personalization to move multi-stakeholder buying committees through non-linear customer journeys.
Today, many B2C businesses are finding that at a certain threshold, the price points and buying cycles of a considered consumer purchase are beginning to look almost like a B2B deal.
In this environment, B2C companies are turning the tables and adopting the latest B2B marketing approaches and technologies, to great benefit.
4 Ways B2C Can Benefit From a B2B Martech Stack
1. Adopt Hyper-Segmentation for a Better Understanding of the Ideal Customer
Most B2C technologies focus on point-in-time transactions across a massive prospect universe. But they aren’t great at capturing detailed profile and activity data on each of those customers.
While they ingest plenty of basic demographic signals from search patterns and lifestyle purchase history, much of that information is anonymous. Anonymization makes it challenging for marketers to understand and analyze the data, since they can’t link consumer patterns with internal data from custom forms or other identifiable insights.
B2B systems, on the other hand, track a complex web of detailed attributes and match activities to purchases across each customer at every stage in the buying journey. They are well-equipped to help marketers segment their total addressable market deeply and precisely across all types of customer signals and behaviors.
A consumer tech or financial services company might want to segment its customers based on their travel profiles (many of which overlap), or a home rental agency might consider not only what types of properties a consumer is interested in, but also what city they live in or which industry they work for.
B2B predictive platforms can deliver valuable insight into these situations by producing easy-to-understand customer predictions that inform the segmentation process so marketers can determine which profiles should receive high-touch, personalized outreach verses low-cost, low-touch campaigns.
2. Automate Customer Journeys to Reach Buyers at Every Stage
As opposed to the point-and-click purchases of the consumer world, in the B2B model, buying processes tend to be more intricate and involve multiple people. B2B marketing automation platforms support a more complicated funnel that helps marketers plan, prioritize and execute campaigns knowing that certain interactions are bigger influencers to winning a customer than others.
Think about the evolution fast-food chains like McDonald’s have undergone over the past few decades. Rather than organizing their prep staff to assemble Big Macs and other menu items based on a rough estimate of what most people usually order and when lunch and dinner rushes occur, most of these businesses have switched to made-for-you systems in which food is assembled as it is ordered for better quality.
B2C companies are poised for a similar transition away from one-size-fits-all marketing as they adopt B2B martech systems to better orchestrate end-to-end, dynamic automation across their many channels and segments. Predictive technologies inform these tailored workflows by showing which assets, campaigns or channels reach a company’s best-fit customers or profiles.
3. Increase Personalization to Boost Advertising ROI
While B2C marketing can rely heavily on brand advertising to push decision makers over the line, in B2B, brand awareness might help get a vendor into consideration, but won’t close the deal alone. Because B2B systems collect all kinds of customer intelligence, they do an excellent job of helping marketers go beyond general brand-building through profiling, predictive modeling and personalization at scale.
B2B martech stacks bring better data and richer profiles to the task of executing hyper-segmentation strategies, workflow automation and dynamic content — all of which combine to deliver both higher short-term conversions and greater customer loyalty over the long-term.
For example, Dell leverages the same marketing automation platform to power both the B2C and B2B sides of its business. As a result, its marketers have a better understanding of their ideal customers and can draw these prospects into more intimate, personal conversations with the brand.
4. Use Full-Funnel Insights to Drive Engagement
With all of the apps launched during the recent martech explosion, integration causes major headaches, leaving dangerous blind spots between some go-to-market workflows. It doesn’t help that many B2C interactions happen offline, compounding the challenge of collecting and interpreting data across the entire customer funnel.
The good news is B2B systems generally “play together” better than B2C tools because they offer more open APIs, and were made from the get-go to deliver end-to-end insights to a sales audience.
As opposed to fueling the sales and marketing divide by keeping people siloed in different B2C systems, seamlessly integrated B2B platforms can bring all of the functions together. For instance, predictive platforms can learn from historical sales data to model what a good customer looks like, and apply that intelligence to the top of the funnel, which then cascades through marketing automation programs and all the way down the funnel to help customer success teams load-balance customers.
B2C companies using this type of intelligence throughout their business will grow consumers’ loyalty, increase retention and find new ways to delight people.
It’s Time for B2C to Flip the Funnel
Over five years ago, Joseph Jaffe started a B2C conversation about “flipping the funnel” (a term which has since been hijacked and distorted by the ABM community), yet few B2C companies have fully adopted the mindset. In comparison, B2B marketers inherently follow Jaffe’s approach, because it is built into the very way they sell.
As more noise infiltrates a consumer’s purchase decision, it’s becoming harder for B2C marketers to drive conversions with mass-messaging. It is time for B2C to take a cue from B2B and finally double down on one-to-one relationships.