How to Make Data-Driven Decisions with PhD-Insights’s Founder Sheana Ahlqvist

27 Feb How to Make Data-Driven Decisions with PhD-Insights’s Founder Sheana Ahlqvist

Whether you run a small, socially responsible company, or a large corporation, you should have a strategy to make data-driven decisions. I asked data expert Sheana Ahlqvist to share some tips on how integrate data insight in your business. Sheana Ahlqvist has a PhD in Quantitative Social Psychology and is a business insights consultant at PhD Insights. She helps companies gather user feedback and make data-driven decisions to achieve their business goals.

Aurora Meneghello: You are a data expert: tell us a bit about what you do.
Sheana Ahlqvist: Running a successful business requires lots and lots of decision-making. Put simply, I help businesses get the information they need to make data-driven decisions and maximize their goals. In reality, that takes many different forms based on the client and the particulars of their business.

For companies that already have data, I turn that into actionable information. Many business with subscription models, like premium Pandora plans or weekly food delivery services, want to retain their subscribers as long as possible. They might already have basic information on their customers, including how much they spend, how often they order, and how they were acquired. I leverage that information to create statistical models and predict not only who will cancel their subscription, but when that will happen. Now, the company is in a position to retain that customer: they can send them a special offer or just reach out to show their appreciation before it’s too late. In this case, data that the company had all along could improve their bottom line.

For companies that don’t have data, I help them collect the information they need. This can take the form of remote user experience testing, online surveys, “fast feedback,” or customer interviews. For start-ups or small businesses, I often collect data to identify their target user: who is the most enthusiastic about your product? Who is the most profitable? I help them identify their core value propositions and utilize A/B testing to help them decide between logos, taglines, and other branding choices. For more established businesses, I leverage user-testing to identify points of friction in their mobile app or online check-out process, and advise their product team. If they have loads of data, we can do some pretty heavy-hitting stuff.

Aurora: How did you get into data?
Sheana: In a very roundabout way! I have a PhD in quantitative social psychology, so my original pursuit was to learn about human behavior. Data is the tool for scientific inquiry: does caffeine make you more alert? Does having a child ruin your marriage? Should a student stay up all night cramming or get a good-night’s sleep? The questions are all different, but the method is the same: collect great data, perform statistical analyses, and draw sound conclusions. Data is how you get the right answers to your questions. I spent 7 years learning data analyses and statistical methods to support my scientific pursuits.

Aurora: You often say “smart businesses make data-driven decisions.” How can businesses leverage data to make better decisions?
Sheana: Business is about making decisions, all of which impact the bottom line. All too often, we’re left using our intuition for such important choices. Intuition is great, but it’s often incomplete. Think of the film Moneyball. Sport experts used to “know” from “years of experience” that a player would be affected by a bad break up, only “had a few good years left,” etc. While those may have been true, it was likely incomplete information. Someone who knew every stat for every player had a much more complete picture, and was in a position to act on information no one else had. Smart businesses have known this for years and are collecting data and acting on it. It’s the only way to stay competitive today.

Regardless of whether your business is large or small, you have to leverage your data to compete. For small businesses, this often means collecting some kind of data in the first place. Do you know your average monthly sales? Is Google Analytics set up on your website? The first step is making sure that you are keeping track of the numbers. Ideally, you use established system (like Google Analytics) that work in the background without much active maintenance.

For large businesses, all too often the opposite problem is true. Many are guilty of just collecting and storing data. They have no rhyme or reason for what they are collecting, and end up with so much data that it’s overwhelming and not actionable. Simply collecting data does nothing. You have to then turn that data into actionable insights in order to make data-driven decisions. I encourage larger companies to understand their business goals and be focused about the questions they ask.

Aurora: Is it possible for smaller companies to be competitive when it comes to data? Or is a large budget necessary?
Sheana: Obviously, big companies can bring the big guns: complete instrumentation to collect data, python scripts that automatically highlight insights, and dedicated data scientists to fill the gap between AI and business questions. For instance, when investing in the stock market, I – as an individual investor – will always have less information on a given stock than Goldman Sachs. In the long run, their insights will always beat mine. But, having additional information will still improve my outcomes. There is plenty that companies can do with small budgets even if they are lacking a data pipeline. For small companies, better insights will get you more customers, higher profitability, and identify additional growth opportunities, regardless of whether someone bigger is doing it even better.

There are two issues: 1) having the data you need and 2) having someone that can interpret it for you. Smaller companies can leverage lots of inexpensive and free tools to collect at least some data. For example, Google Analytics is a must have for any website. It can tell you where your traffic is coming from, who is staying there the longest, and is completely free. For mobile apps, you can add product analytics solutions like MixPanel or Clever Tap, both of which have generous free tiers.

On the talent side, start-ups and small businesses won’t need a full time data person. If you have a team member who’s excited about data, they may be able to incorporate that as one of their ongoing job responsibilities. Hiring a consultant is another option, and it ensures you’re getting expertise. You can also bring them in for short-term projects or only when needed, perhaps to coincide with a new product launch or in time to review quarterly business goals.

Aurora: What resources would you recommend for business owners and entrepreneurs who want to learn more about transitioning to making data-driven decisions?
Sheana: The Lean Start-up is a new classic for testing and iterating quickly. If you don’t have time for the book, try the one-hour-lecture version. Mixpanel offers great 20-minute lectures featuring best practices from the most innovative companies. Check out the one by Airbnb.
Luke Wroblewski is a great resource for leveraging best-practices for web/mobile, if you don’t have the resources to collect your own data.
Want a deep dive? Taken an ivy-league course on data science and analytics online through EdX.

Aurora: You are passionate about reducing the gender gap in STEM, and even wrote your PhD dissertation on this topic. What needs to happen, and what can we do to close the gap?
Sheana: First, it’s worth mentioning why this is important. Technology increasingly touches every job, and we expect that the future will require even more experts in technology across every field. We need to have as many experts as possible. By having more women in these fields, we’re in a better position as a society to fill the jobs of the future.

Closing the experience gap is a big deal. Boys are getting experience, for instance, learning to code, earlier than girls and this advantage compounds as they enter their first classes in high school and college. K-12 schools need to start teaching coding as part of the mandatory curriculum. Right now, boys are discovering code in their free time and bringing that experience to school when it’s finally offered in high school or college. Then, girls (and boys without that experience) learning to code the first time it’s offered find themselves falling behind relative to their classmates, who may have already had lots of experience. By giving everyone a baseline of knowledge earlier on, we can reduce the likelihood that this happens. Similarly, large companies that want to close the STEM gap can continue offering girls and other non-coders hands-on training through internships or work-study programs. Then, when women apply to their first STEM jobs, they’re in a better position to complete with the men around them.

For those who are interested in improving the diversity at their organizations using evidence-based practices, I recommend Mary Murphy and Greg Walton’s 15 hacks for building diversity in tech. As a bonus, most of the practices that improve diversity are good for all employees, regardless of background.

Aurora: As you know I am all about helping companies that are out to do good, while making a profit, grow and prosper. Any advice for non profits and social entrepreneurs on leveraging data to make a difference?
Sheana: Non-profits and social entrepreneurs should first and foremost hold themselves to the standards of success of highly profitable corporations: set specific goals. Track your success. Identify inefficiencies. OKRs are a great place to start, in which team members are required to set ambitious, quantifiable goals (see this classic talk on OKRs).

The Robin Hood Foundation, which focuses on eliminating poverty in New York City, is the perfect example of a non-profit taking their data and metrics seriously. They look at their investments and philanthropy with the same calculated, brutal eye of a hedge-fund manager. The result is the most effective programs possible for every dollar spent. You can learn more about how they assign value to their efforts on their website. You can also even leverage some of their past learnings, which they’ve made public, to learn how you can make data-driven decisions as well.

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