Knowing your audience is one of the keys to B2B marketing success. But knowing the company they work for and their job title no longer cuts the mustard. You need to know their job function, their pain points, what content they consume, where they consume it, what triggers a purchase decision and many more things before you can really claim to understand what makes them tick.
That’s the challenge Pulse took on in January 2017 when Couchbase delivered a brief to raise awareness of its NoSQL solution among a new, higher value audience.
Couchbase wanted to boost net new customer acquisition, upsell and cross-sell within existing customers and, ultimately, significantly increase average order value (AOV).
What followed was a new form of ABM programme which:
- Identified the best fit accounts to target.
- Compiled detailed analysis of the decision-making units (DMUs) in those accounts, creating robust personas.
- Built/repurposed content by persona and stage of the buying cycle to ensure it addressed their precise pain points.
About
Couchbase’s mission is to be the data platform that revolutionises digital innovation. To make this possible, Couchbase created the world’s first engagement database. Built on the most powerful NoSQL technology, the Couchbase data platform offering includes Couchbase Server and Couchbase Mobile and is open source. The platform provides unmatched agility and manageability – as well as unparalleled performance at any scale – to deliver ever-richer and ever more personalised customer experiences.
Strategy
NoSQL has far-ranging business benefits. However, as it’s traditionally been aimed at very technically-minded individuals, the AOV is lower than the industry average.
Couchbase had a handful of high-value customers, but a long list of customers with a low deal value. To increase the AOV, Couchbase needed to cross-sell and upsell into high-value existing customers, as well as generate net new accounts.
The challenge was that Couchbase was competing with large heritage SQL providers – such as Oracle – together with other NoSQL companies with a larger brand presence. Trying to upsell and cross-sell while being relatively unknown in a new category was a huge challenge.
Objectives
ABM had already been identified as a potential vehicle to help Couchbase focus on high-value customers.
While Pulse felt this was a good starting point, the company suggested it should not be the only method to generate net new customers. A much deeper level of insight was required and so Pulse ran some preliminary planning work and highlighted a few objectives.
- Pulse needed to build a campaign that helped Couchbase compete with more established competitors.
- Couchbase previously targeted technical IT. Pulse’s campaign needed to expand this to strategic IT and strategic business.
- Existing content and messaging had a technical focus. Pulse needed to adapt this to the more strategic, high-value audience, based on first-party insights.
- Deep data insights were needed to build an account list, and to determine the right people within these accounts.
- In-depth understanding of the content consumption habits of target accounts was very light. Pulse needed to ensure content spoke to these people on a personal/human level.
- Pulse’s activation plan needed to deliver the right messaging/content to the right person, at the right time.
Pulse felt a broader one-to-many (or programmatic) ABM approach would help Couchbase put some of the foundations in place. These foundations could then support an ongoing ABM strategy, and be repurposed (if necessary) for a vertical approach or even the few focused ‘high value’ customers.
The target audience
Audience can be defined by two things: the right accounts and the right people within those accounts. In this campaign, Pulse recommended focusing on customers with the highest likelihood to convert.
These customers typically work for huge enterprises and are constantly approached by Couchbase’s competitors, many of which are larger, more established companies with bigger marketing budgets. The strategy needed to be extremely efficient and supported by a deep level of insights.
Media, channels or techniques used
Account segmentation
To establish the right account segmentation, Pulse asked Couchbase for a list of ideal accounts, as built by sales. Couchbase already used predictive analytics (Infer), and was asked to add an intent engine (Bombora) to provide an extra layer of intelligence. This created a new level of insight; Pulse could combine Bombora’s context with Infer’s predictive modelling.
By creating keyword lists for Bombora alongside Infer’s propensity to buy models, Pulse created a unique account segmentation ranking of all of Couchbase’s identified accounts while highlighting completely new accounts.
Personas
Pulse ran persona workshops with all customer-facing personnel to start understanding the roles, pain points, reservations, buying cycle relevance and content consumption habits of each function in the DMU. This was supplemented with data generated from Couchbase’s CRM, as well as manual and automated social listening against target accounts.
The result: actionable one-page personas that could be used by the entire workforce.
Content research
The intent data on accounts that were highly active around certain keywords, plus social persona data and search-based volume data, helped Pulse create a robust content research document. This removed the gut feel from content creation and informed Couchbase on exactly the right content to create for each persona within identified accounts. And when and where to deliver it.
Armed with this, Pulse ran a content audit reviewing every Couchbase asset by persona/buying stage/pain point, while also looking at existing content consumption data from their CRM.
Activation plan
What’s the point of engaging, relevant and authoritative content if it never gets seen by the intended audience? Pulse’s insights allowed the company to create persona-led activation plans for the content suggested.
Subsequently, as Pulse began to run programmes, it was able to understand whether its account selection models were accurate and refine accordingly.
If there’s one thing to leave you with: it’s that every single body of work was linked, no data point was ignored and everything was questioned.
Timescales of the campaign
This campaign started in January 2017 and is still active but all above work has been completed.
Budgets
- Strategy and Insight: $25,681
- Content Messaging: $14,857
- Activation (incl media): $94,013
- Reporting and Analytics: $14,046.
- Overall: $148,598
Results
The campaign has seen some excellent account level engagement. To date, some very detailed reporting has been pulled together to show which accounts are engaging, where those accounts were originally (new or existing Couchbase accounts) and their relevant account score.
Other results:
- $1.5m worth of sales pipeline and the campaign is now moving into phase two of account acceleration for those highly engaged accounts.
- ROI of $10.5:$1 and a 1371% increase in AOV.
