How to leverage your data in an economic downturn

If data is the new gold, then controlling your organization’s data is invaluable, especially in the face of economic uncertainty. For startups, that time is now. Capital is much harder to come by, and founders who were receiving unsolicited term sheets just a few months ago are suddenly looking at how to extend the runway. Now, thanks to new privacy laws and restrictions imposed by Apple devices, it’s also harder to engage an audience.

So what’s a founder supposed to do – snuggle into the fetal position and lay off half of his staff? Slower. Stay away from Twitter. Recessions and downturns leave their mark on everyone, but truly spectacular companies can and do emerge during economic downturns—and your business can be one of them with the right data strategy.

Your data can be the superpower of your business. When used properly, data can help go-to-market teams do more with less, such as:

• Customize onboarding and product experiences to increase conversion rates
• Understand where users are struggling and proactively help
• Apply selling pressure at the right time and get expansion income that came naturally a few months later

However, in many organizations, user data is most commonly siled within product and development teams, kept separate from marketing and sales, and not often linked to monetization outcomes. It doesn’t have to be your company. Good hygiene and efficient, sensible data setup can help your team ensure data is accessible and available to everyone who should be using it.

product measurement

A major problem companies face when democratizing data is converting actual product usage into business value. If a user uses a key feature in your app, that’s good, but if they do it 50 times in the first week, that’s excellent. Simply measuring usage and storing it somewhere dampens the value of these key activities.

For this reason, it’s helpful to have a cross-functional team meeting while setting up your data structures to account for facts and metrics.

Define facts vs. measures

The facts are simple: they are actions that are performed in your product. For example, using features along with the user’s ID and an organization’s ID are all facts. Engineers and product managers are usually pretty good at identifying and capturing facts in a data warehouse.

Actions, on the other hand, are calculations that emerge from the data. Metrics can tell the value of the facts they are built on or illustrate how important that particular step is in the user’s journey.

An example of a measure can be as simple as a person’s qualifier, e.g. B. “She chose to search for a business use case when onboarding” in a column named “Business or Personal.”

Measurements can be more complicated, such as a running count of a user’s visits to a pricing page, or a threshold for whether or not they’ve been activated.

I always recommend that organizations leave the engineering and fact tracking to the creators of the product – engineering and product – and then build a team around the actions. The best teams treat actions like a product itself, with user interviews happening across support, marketing, and sales to learn how these customer-facing and go-to-market teams see and use that data, and a roadmap to create actions that matter .

Implementation of data collection and distribution

Once your team has determined what they want to track, the next key question is, “How can we store this?” It feels like there’s a new data solution coming out every day, and less tech-savvy audiences and founders might Heads are spinning when it comes to options for storing, capturing, and visualizing their data.

Start with these basics:

• Data (the facts) live in a data warehouse
• The data is then transformed into metrics using an ETL (Extract, Transform, Load) tool, and these metrics are also stored in the data warehouse
• When needed, metrics and facts can then be pushed into people-centric tools to democratize them with a reverse ETL tool

There are tons of data warehousing, ETL, and reverse ETL options in the market to move the data, so I won’t mention any vendors here. This is where it’s important to involve not only your engineering team, but also product teams and the roundtable you set up to productize your actions. That way, no one misses out on actionable data in the tools they use.

Act with your data

The last and most complicated step after storing your facts and identifying and creating your team’s ideal actions is to make that data available where your team works on a daily basis. This is where I usually see the biggest drop. Getting sales, support, and success teams to log into a daily dashboard and take action on the data isn’t easy. Getting the data into the tools that already use it is crucial.

This is where data democratization becomes more of an art than a science. Your creativity in using your own data will help you take control of your company’s destiny. You’ll need to use reverse ETL to integrate these measures into a CRM, customer success platform, or marketing automation tool, but what you do with them is entirely up to you. You could create dynamic campaigns for accounts that find value with the tool, or provide highly active users for direct contact with the sales team.

In a downturn, it’s extremely valuable for support and success teams to understand if a customer is using your product tool less than usual, or if a key player is no longer in the customer’s organization.

Remember:

• Look outside of product and engineering to think of critical use cases for your data
• Include players from across the organization when setting up a reporting structure
• Data democratization dies when data is isolated in a dashboard

As an industry, we’re fixated on the companies that are doing amazing things with their data, but we don’t talk often enough about the underlying structures and frameworks that have gotten them to this point. All of these playbooks are enabled by data, but can only be implemented if you have proper data hygiene and structure in place, and put information in the hands of the right people at the right time.

Sam Richard is the VP of Growth at OpenView.