Taking a data-driven approach has enabled me to elevate marketing’s role by proving its impact on revenue and supporting a culture of optimization and collaboration.
I think back both fondly and critically on the dot-com era. Relatively young and in the early part of my career, I recall approaching my CEO with my boss, the VP of Marketing, to ask for a signature on an advertising contract. Without asking about the cost or ROI—without even glancing at the contract—the CEO gave us the go-ahead. The contract was for a $2.1 million Super Bowl ad.
As it turns out, we didn’t end up moving ahead with the agreement, but it’s a perfect example of the mentality that characterized that wildly optimistic time.
When the bubble burst, I could look back and recognize that there had been no accountability for spend—not just for marketing, but across many lines of business.
I used that early insight to build a career based on identifying the marketing metrics that supported company goals and holding myself accountable to those metrics. (It didn’t hurt that my next CEO was a mathematician, so a disciplined approach to measuring and reporting was essential for me to secure any spend.)
For many years now, my approach to marketing has been driven by data. Taking a data-driven approach has enabled me to elevate marketing’s role by proving its impact on revenue and supporting a culture of optimization and collaboration.
Here are some of the key elements I learned over time that go into an effective, data-driven approach to sales and marketing.
Start With Revenue
To be successfully data-driven, you need to focus on the right data. When I talk to my peers at growth companies, I’m surprised by how many of them don’t work backwards from revenue. If you’re working for a company with ambitious revenue goals and you’re not aligning the metrics you track with those goals, how can you prove marketing’s relevance?
You can track email open rates and web traffic, for example, but how are they contributing to the company’s revenue goals? Unless that activity connects to the sales pipeline—perhaps by driving more clicks and form-fills—it’s not a meaningful metric. Start with revenue, and let those revenue goals dictate the metrics that are most important to collect.
Unless that activity connects to the sales pipeline, it’s not a meaningful metric.
Revenue is easy to measure, but you can’t wait for an entire sales cycle to complete before seeing whether you’ve hit the goal. Putting KPIs in place helps you see whether you’re on track to reach that revenue goal weeks or even months before the sale actually closes.
Start by modeling the revenue expected from existing customers vs. new logos and understanding the goals for each customer type or segment. Using the historical data that’s already in your system, analyze your average deal size, time to close and the number of leads required. At WorldAware, we track the lead lifecycle through each qualification stage so that we can determine the rate of attrition we should expect as leads move through the funnel, from qualifying to vetting to opportunity to closed won.
KPIs help you see whether you’re on track to reach your revenue goal weeks or even months before a sale actually closes.
There’s no right way to map the sales cycle—it’s different for every organization—but what’s important is to align sales and marketing around the data points and the process used to collect them so that you can coordinate your activities, collaborate on solutions and present a united front to the executive management team and other stakeholders.
Test Early and Often
Being data-driven supports an agile approach that enables marketing to take more chances and explore more opportunities by either failing fast or, more positively, accelerating success. At WorldAware, we have anywhere from five to eight different channels driving demand into the business, and we’re always looking for new channels. We test every new engagement, such as an account-based marketing program or content syndication, on a short timeframe (one or two months, primarily) so that we can collect our initial metrics on the performance of each new channel, each new asset, each set of ads or promotional copy and each new audience segment.
Being able to measure the impact on each stage of the sales cycle means that we can quickly determine whether a specific program is generating leads, and whether those leads are progressing through the pipeline in acceptable numbers. If the early results are positive, we keep the program in rotation; if we don’t see traction, we move on without having wasted a lot of money. The ability to track the impact of various channels and campaigns enables us to continuously improve the marketing mix.
Being data-driven enables marketing to take more chances and explore more opportunities by either failing fast or accelerating success.
Collecting performance data doesn’t just give you the ability to be more agile and experimental in trying new campaigns and channels, it also enables you to continually adjust the approach and improve the results over time. While we always have goals in place, we always want to exceed them.
We analyze the leads generated by each lead source and each campaign and track them across the lifecycle so that we can identify places where there is room for improvement. We’ll look for patterns: Are fewer leads being generated from a particular geography or industry? Are opportunities falling out of the pipeline earlier than normal, in which case we may need to look at our qualification criteria? Or are contacts or opportunities not converting only for a particular sales team, in which case individual coaching may be needed?
For example, our inside and outside sales staff have historically split the responsibility for new logo development 50/50. But we hypothesized that if we shifted the split 35/65, with Sales Development Representatives (SDR) ramping up their contribution, it would give our account executives more time to cultivate and accelerate qualified leads. We implemented the new system and determined that the early KPIs were trending in the right direction. This, in turn, enabled us to prove our hypothesis sooner and invest more resources into growing the SDR team ahead of schedule because we were able to project the potential return.
Tracking and analyzing pipeline data doesn’t just help you improve performance, it also helps you predict it more accurately. Once you have enough historical data to be able to identify the patterns, you can forecast sales more accurately based on tested data, such as the ages of the opportunities in the pipeline and the stages that they’re currently in. You may discover that an opportunity that’s 90 days old and in stage 3 of your lifecycle has a 10 percent chance of closing, for example, and that is data you can factor into your forecasts. Using the data, rather than your own intuition or that of your sales team, to forecast revenue enhances your credibility in front of your boss or the executive team and, more importantly, helps you identify and address issues sooner that may jeopardize your ability to reach the revenue goal.
Once you have enough historical data to be able to identify patterns, you can forecast sales more accurately based on tested data.
Here’s the bottom line.
When sales and marketing activities are driven by data and tied to revenue, it transforms the possibilities. By using historical data to map your lead lifecycle and fresh data to track your performance against the benchmark, you can ensure that marketing is accountable to and aligned with company goals. Continually reviewing and measuring the data and adjusting the metrics you collect as needed also helps you to become more agile in exploring opportunities and—where necessary—pivoting quickly to ensure your focus is appropriate and the desired outcomes are met.