Why your startup’s organizational strategy should include analytics

By Danny Bradbury

So, you’re a hungry startup eager to establish your product and build your audience. Entrepreneurship is a daunting journey with many wrong turns along the way. How will you know whether you’re making the right decisions? Analytics can be your friend, but only if your organizational strategy supports it.

Measuring your progress is crucial if you’re to understand what’s working and what isn’t. Unfortunately, it’s easy for startups to make mistakes with their analytics, according to Pierre Lechelle. Common issues include tracking the wrong metrics — such as the vanity metrics identified by TechCrunch — or tracking too many, which provides a flood of data without telling you what’s important.

Here’s how to build an analytics strategy that will separate your startup from the crowd:

Getting serious about metrics

More than any other type of company, startups need focus. They’re working with high burn rates, constrained resources and low margins for error. In his Lean Startup methodology, Eric Ries articulates the entrepreneurial cycle of building products, measuring their success and learning from the results before building again.

That type of positive feedback requires a laser-sharp approach to analytics that tells startups what they want to know — and quickly. Keep your analytics process lean by focusing on day-to-day operations and prescient questions using cheap or free event-driven analytics tools. Scale up over time as your business changes and revenue grows.

As KissMetrics said in its guide to startup analytics, use metrics that measure your biggest problem and ignore everything else until further down the road.

So, what’s your biggest problem? These will change over the course of a startup’s life, and they will affect the types of metrics that are important. For example, an early-stage startup shouldn’t be as interested in growth as it is in what to grow. It will be preoccupied with validating its idea and then ensuring its product is developing in accordance with customer needs.

When working out whether your idea is any good, you’ll need to talk to end users. As you build out a product to support your idea, you’ll ask questions such as “Which feature is most used?” and “Why aren’t users accessing this particular function?”

In this early phase, engagement and feedback data will be particularly important.

Developing an organizational strategy

This brings up the question of where your metrics come from. In the early days, you may find there isn’t always a lot of them. Sometimes, individual user analysis rather than aggregated data-gathering may be your best bet.

If you’re a startup building a mobile product or SaaS offering, you have the advantage here because you’ll have the opportunity to gather that feedback data directly from within the platform. You can tell exactly what users are doing with your product from an early stage.

Which questions become more important as your product and company become more established? Growth will soon be on your mind, followed by business stability. This will make other metrics more important, such as customer acquisition and retention and return on investment. At this point, when the product is stable and you’re trying to gain traction, you may find yourself redefining your key performance indicators.

For any of this to happen, though, a startup must have the appropriate culture and organizational strategy to make analytics useful. That can be harder to create than it looks. Many companies fail to structure their analytics operations properly, leading to dissatisfaction.

The startup advantage

Startups have an advantage here because their cultures are constantly developing. They are small, nimble and malleable. Use this opportunity to develop a data-driven culture by ensuring metrics are not only available to everyone, but are actively used to make decisions for your young business.

Ensure everyone has access to the same data and is encouraged to use it to make decisions. Assigning a single team to the maintenance and cleanup of high-quality data is an important part of the process. The earlier you prioritize data aggregation by assigning ownership to it, the more likely you are to avoid creating future data silos as your business expands.

That team should be well-financed as well. Analyzing and collecting data isn’t something to be taken lightly, according to marketing guru Andrew Chen, who has advised dozens of companies on analytics and now works on Uber’s growth team. Chen says startups should devote between 25 percent and 40 percent of their technical resources to the task, meaning that for every engineer you commit to product development, you devote one to analytics.

Startups can supercharge their product development and growth with analytics. It just takes some forethought and a commitment to build an organization that takes the data seriously. Are you ready to get serious about your metrics?

Written By

Danny Bradbury

Freelance Writer

​Danny Bradbury has been a technology writer since 1980. He covers a variety of topics ranging from enterprise to consumer tech. Specialist areas include cybersecurity, software development and mobility.

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