How I Ran Effective B2B Marketing Experiments

How I Ran Effective B2B Marketing Experiments


This is the fourth and final part of my blog series on Marketing Planning for 2024, the first of the series here.

A few years ago, I had a classic marketing problem. At the time, the large enterprise software company I worked for did not have an SDR (Sales Development Representative) team, and the automated nurture campaign did not deliver. It was a constant source of frustration that thousands of top-funnel leads generated by marketing for the region remained untouched. Understandably, the sales team wanted to avoid following up on low-intent leads such as webinar attendees or leads who downloaded assets. Meanwhile, passing them to the numerous tiered APAC partners was too complicated and would take too much time. How did we manage this problem?

This is where experimentation came into play. I decided to experiment with an AI tool (years before AI was hip and before the ChatGPT Era!). A Singapore start-up delivered this AI tool (I was one of their first customers), which enabled me to create a robot (a virtual team member) that ‘personally’ engaged, qualified, and converted these underserved marketing leads into sales meetings via email. It worked like magic. Within weeks, we re-engaged with over 30% of the stalled leads, creating pipeline and sales-ready opportunities for the sales team and partners.

I won an award for this initiative, the most innovative campaign of the year. But most importantly, this shows just how important experimentation is to be a successful marketer.

Marketers must embrace contrarian ideas and experimentation to truly stand out internally and to the market. “What works” in marketing is ever-evolving; business landscapes are constantly shifting, technology is changing fast, and ever-increasing expectations for marketing are continuously increasing. I found that infusing a culture of experimentation into all areas of our marketing efforts tends to pay off. Experimentation is part of good marketing and the only way to uncover breakthroughs.

Top Analysts such as Forrester recommend that marketing teams allocate at least 10 to 20% of their 2024 marketing budget to experimentation.

However, despite experimentation being such an important element of growth, I understand why many B2B marketers shy away. Running experiments in B2B marketing is not easy because the B2B buying process is very complex. As we know, B2B buying involves a buying committee with numerous decision-makers and influencers, often seven or more people, who come from different departments. They engage with the company via tens to hundreds of channels.

But the real challenge – especially for revenue-focused B2B marketers, is the long sales cycle in B2B – the time it takes from initial contact to sealing the deal.

Considering these complexities, many marketers naturally prefer to opt for shiny new tools,  follow what competitors are doing (this is not entirely wrong, by the way; read my previous article about stealing great ideas from competitors ), or stick to the status quo.

Setting the Stage for B2B Marketing Experimentation Success

From my experience, there is a way to enhance the success rate of your marketing experiments, and it helps to have a structured approach as the foundation of continuous improvement. 

Get that Stakeholder Buy-In

First, get your stakeholder buy-in, especially for high-cost experiments. Show the potential outcome and the problem it is addressing. And share the best and worst-case scenarios. By stakeholder, I include your leadership, sales, and/or your team members.

Secondly, let’s talk about Metrics.

You need to understand your sales cycle length or duration f. It should be agreed upon by all stakeholders and form the basis of your experimentation programs. 

Once that is agreed, considering the long sales cycle, top-funnel metrics like lead generation, marketing-qualified leads (MQLs), and sales-qualified leads (SQLs) can substitute for lower-funnel metrics. These top-funnel metrics show quicker results, are easier to track, and can be optimized multiple times within a single sales cycle. They can provide hints about what’s happening, and by looking at historical data, you can safely measure the opportunity that will be generated and estimate the revenue impact after a certain period.

No matter what metrics you choose to measure the success of an experiment, they should align with the impact on revenue.

Achieving alignment of goals between sales and marketing teams at each stage of the sales funnel is very important. Identify the revenue-linked metrics crucial to the entire business, not just individual functions. This alignment ensures that everyone shares a common perspective and, down the road, focuses on lower-funnel metrics that influence revenue outcomes.

Implement a Reliable Attribution Model

Due to the intricate nature of B2B customer journeys, a comprehensive attribution model capable of aggregating various online and offline marketing activities across the entire sales funnel can be very beneficial. Correctly identifying and measuring the revenue impact of each marketing activity with a marketing attribution solution will give the team a fair view of what marketing initiative is contributing to the business.  (I am so glad that attribution models are available today, which was not available earlier in my career!)

Find the Sweet Spot of Optimization

Many B2B marketers overlook optimization cycles when planning experiments, often choosing metrics at random without considering the broader context or metrics isolated from the context of the giant funnel. The full funnel view also helps define and connect the cycles through the entire sales cycle duration.

The revenue marketing methodology is better because it lets you measure as close to revenue as possible without sacrificing the number of optimization cycles you need throughout the year.  This is the ‘optimization cycle sweet spot’ for your company.

Execute Pipeline Acceleration 

To expedite results, a proactive pipeline acceleration strategy can be employed to shorten sales cycles and facilitate more testing cycles. This accelerates feedback loops, simplifies the buyer journey, and reduces complexity. 

Manage Unpredictability by Planning for different Scenarios.

Incorporating scenario planning is essential to combat the unpredictability of the market. Having a contingency plan in case assumptions prove untrue, such as a competitor’s significant acquisition, a recession in key geographic markets, or the loss of a critical channel partner, can improve the chances of predictable growth.

Conclusion: Seize the Power of B2B Marketing Experiments

In today’s revenue-driven landscape, B2B marketing experimentation may present challenges, but not optimizing for revenue-related metrics is no longer an option. While there’s no one-size-fits-all solution for optimizing revenue-related metrics in lengthy B2B sales cycles, the methodology shared in this article can help you run a cohesive and successful experimentation program.

As revenue-focused marketers who have embraced this methodology can attest, optimizing the right metrics in the full funnel and sales cycle length establishes a clear connection between marketing activities and revenue and instills the confidence to invest in effective strategies throughout the funnel.

With the methodology outlined in this article, marketers can harness the power of B2B marketing experiments to fuel success in 2024 and beyond. Would you have any thoughts, comments, or other tips for successful experimentation? I would love to hear from you!

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