Original posted on Medium.

Transitioning a start-up from validated idea to actual business means you’ve demonstrated that you can successfully grab the attention of prospects, run them through a marketing and sales cadence and close deals at some predictable level of certainty. Core to that growth strategy is starting a demand generation machine that brings eyeballs to assets and delivers a predictable size audience. However, startups often encounter a unique set of challenges in understanding what works and what doesn’t in their initial demand generation efforts. The uncertainty arises from the difficulty in pinpointing what isn’t working across tools, messaging, or channels. In this blog post, I hope to expose what many of us go through as we delve into this predicament and explore potential solutions to overcome it.

1) The Complex Web of Factors

In a startup environment, multiple factors intertwine to shape the success or failure of demand generation efforts. Identifying the precise cause of underperformance becomes daunting due to the interplay between various elements, and any lack of baseline. With no history of what ‘good’ looks like for a new business, any initial effort where messaging has gone out through a specific tool, on a specific channel has no ‘comparison’. Results from those efforts are hard to read often because there is no pattern yet. Lack of replies to an email might be a factor of the tooling (did the message go to spam), the message (it just didn’t resonate) or the channel (people ignore emails).

2) Evaluating Tools

Startups often experiment with an array of demand generation tools to optimize their outreach. Using email automation is a low cost option for many startups but the environment around email marketing is getting increasingly more difficult given automated spam detection. So factors like not being able to send too many emails at once to avoid having your domain blacklisted can slow down your learning curve. Data coming from 30 emails doesn’t really tell you anything now does it? Finding tools that help you automate building lists, scraping sites, setting up campaigns are all things to look for, along with how the tool helps you avoid damaging domain reputation.

3) The Messaging Conundrum

Crafting compelling and resonant messaging is essential for capturing the attention of potential customers. This is core to how you market and sell in the future and is something that quickly becomes the most important tactical work that needs to be done. Startups often struggle to ascertain whether their messaging is the root cause of poor demand generation results because there’s no history to compare it to. A regimen of A/B testing, throwing out lowest performing messaging, iterating and gathering feedback from customers and prospects can provide valuable insights into the effectiveness of messaging strategies.

4) Channel Dilemma

Another factor when you are just starting out is finding the channels that matter to your audience. Startups typically explore multiple channels to reach their target audience, such as social media, email marketing, content marketing, podcasting and more. Because channels are intertwined with messaging and there is no baseline to understand performance across either of those vectors, pinpointing which channels are driving the best outcomes is extremely difficult. Again a scientific, regimented approach where measurement of the same message across different channels is required. Only time will give you the baseline you need to make improvements, but you need to be tracking results and eliminating to many variances to determine root cause. That being said, the struggle is real.

5) Solution: Data-Driven Approach

The common theme here is to make sure you are tracking everything you’re doing with the goal of establishing what is ‘good’ and what is ‘bad’. That requires not only tracking but time and rigor. Once you have good and bad, from there its about getting better and better and moving your learnings into new experiments and new workflows.

Conclusion

Navigating the challenges of understanding what is and isn’t working in demand generation within a startup environment is absolutely necessary and absolutely challenging. With the intertwined nature of tools, messaging, and channels, it becomes crucial to adopt a very regimented approach. By tracking and analyzing metrics, experimenting with different strategies, and gathering customer feedback, startups can gradually unlock what will work for their business. Through continuous iteration and refinement, startups can build a robust demand generation machine that will drive sustainable growth and success.