Data Mistakes to Avoid

The Four Cringe-Worthy Mistakes Too Many Startups Make with Data

Insight from Amanda Richardson

At Uber Freight, I lived in data tables. I always tried to discover new insights I could bring to the team. This is where I learned the right way to bring data into my decision-making.

In building The Bottleneck, I've been bringing the same mentality.

Before getting too in the weeds with data, I wanted to refresh myself on best practices.

I stumbled upon Amanda Richardsons essay about the four key mistakes to avoid in data management:

As the Chief Data and Strategy Officer at HotelTonight, Amanda Richardson manages hundreds of data interactions for an app millions use monthly. She sees patterns and data-handling mistakes that are common and costly, leading to missed chances for companies.

The four key mistakes are:

1. Start with a Clear Goal: It's essential to have a specific aim, like boosting user conversion or revenue per user, right from the start. This ensures you stay focused on what you initially set out to achieve, even as new data comes in. You need to create the scorecard by which you’ll judge success

2. Be Cautious with Personalization: Personalizing user experience sounds great but isn't always necessary, especially for new startups with little data. You need a lot of data to personalize effectively, so think carefully about whether it's the right move for your stage and goals.

3. Everyone Can Be a Data Analyst: You don't need to rush to hire a data scientist. Startups can benefit from utilizing the diverse skills within their current team. Promoting a culture where everyone feels able to contribute to analysis and strategy might be more effective than assigning the role to a single person.

4. Choose Your Tools Thoughtfully: Focus on what's truly important: clear and consistent use of data. Having a central dashboard for your main metrics, making data easily accessible to the team, and using tools wisely, no matter how simple, are key to a solid data strategy.