How data drives decisions at 6 Chicago tech companies

June 14, 2018

“Without data, we would just be guessing.”

To Margaret Jastrebski, ShopRunner’s SVP of enterprise product, turning to data before making critical business decisions is a no brainer. But although few leaders would admit to making their business decisions on whims, some companies take a more analytical approach than others.

We spoke to a few of them to learn more about how they use data as a compass.

 

shiftgig chicago tech company
image via shiftgig

Shiftgig is a two-sided online marketplace that connects companies with on-demand workers to cover open shifts. Chief Technology Officer Rick Bowman said his teams devise hypotheses about the expected impact of new features to create a benchmark against which to measure results. From there, the startup continues to iterate on each feature, constantly using data as a guide.

 

How does your team incorporate data into its decisions?

Our product roadmap is determined based on specific business targets. Before building a new feature, we generate a hypothesis for the impact it will have on our business goals. We then use data to measure the performance of the feature after it is released. The data and results of these features help determine the prioritization of our future product roadmap.

 

Can you highlight one particular data-driven decision that has really helped your company grow?

There are many features in our current product that were not only built based on a hypothesis from our data but continuously improved upon after they were released. For example, our data showed there were many people downloading the Shiftgig app without first applying to work for us on our website. From this, we decided to build a feature that allowed workers to go through the application process directly from our mobile app. Since launching the feature, we've seen a major uptick in applications. We've also been able to track where in the application process people drop off. This data has allowed us to tweak the feature in ways that have allowed the number of candidates making it all the way through the funnel much greater.

 

one north chicago tech company
image via one north interactive

As a former product specialist, One North Interactive Senior Data Strategist Ben Magnuson works with clients to implement more data-driven strategies. In many cases, Magnuson said, companies already have the information they need to make better decisions. The key is to teach them what to look for, and where.

 

How does your team incorporate data into its decisions?

Having spent some time in product development in a previous role, I recognize the importance of using data as the foundation for any decision you make. When I joined One North, I was inspired to help our clients — professional services organizations — take that same approach with their businesses. Through the process of building out the data strategy function here, we’ve been able to provide clients with the resources necessary to become familiar with and leverage data that is already available within their organizations. Using this guidance and insight, they’re able to uncover opportunities to improve engagement and, ultimately, their bottom lines.

 

Can you highlight one particular data-driven decision that has really helped your company grow?

In one recent example, a client of ours had been putting a lot of effort into podcasts for its website. Under each podcast, it offered a transcript of the conversation held during the episode. Using analytics, we noticed that users were scrolling on this page less than others, and we hypothesized that the design was not clear enough for them to realize a transcript was provided. By merely adding a label to indicate this was the case, we were able to increase views of the transcripts by nearly 20 percent.

 

silkroad chicago tech company
image via silkroad

SilkRoad makes software that helps HR teams streamline their processes. According to Phil Beckman, VP of research and development, the company relies heavily on data to better tailor its products for customers. One recent development SilkRoad has been keeping an eye on is the industry’s shift toward continuous onboarding.

 

How does your team incorporate data into its decisions?

SilkRoad is a very data-driven company. We capture information about nearly all aspects of the business in terms of customer turnover, customer issues, customer requests and product feature usage. We use that data to drive decisions not just for the product roadmap but for how we structure our organization and the processes we use.

 

Can you highlight one particular data-driven decision that has really helped your company grow?

We recently focused our efforts on strategic onboarding, which is the concept of onboarding as a continuous journey rather than treating it as a one-time event that happens when you join a company. This focus is driven by data that we have about the market’s needs as well as data about how our customers use the products we have today. For example, we’re able to leverage data and market insights to understand when turnover is likely to occur, and, as a result, have been able to develop solutions to continuously engage employees through these transitions or inflection points to drive retention and productivity.

 

shoprunner chicago tech company
image via shoprunner

ShopRunner’s member subscription service gives shoppers free two-day shipping and returns at more than 140 online stores, including Ann Taylor, the NBA Store and Saks Fifth Avenue. In a data-rich environment like online retail, there’s no shortage of ways to experiment with new approaches. According to Margaret Jastrebski, SVP of enterprise product, data makes its way into her team’s every decision.

 

How does your team incorporate data into its decisions?

Product management is responsible for answering the “why.” We influence and drive the rest of the organization to build the products and features we want to take to market. Without data, we would just be guessing. Our product team is all about spotting trends and patterns, and then figuring out how to capitalize on them. We then turn to user research tests to get qualitative validation. We run prototypes to track ease-of-use, understanding, and adoption. We send out user surveys to get direct feedback.

Once we have conviction on a feature, we work with an alpha set of retailers to roll the it out. We track use, adoption and customer journeys before moving to betas and general releases. We validate our initial assumptions and set new ones, and use A/B testing to optimize over time. Every piece of information — qualitative and quantitative — that comes back to us goes into the roadmap decision-making process. Given our limited bandwidth, is it worth investing in this?

 

Can you highlight one particular data-driven decision that has really helped your company grow?

A great example is the recent launch of our Notifications product. A really significant number of consumers in our network were looking for items that they ultimately couldn’t purchase because they were out of stock. So we designed a product that lets shoppers sign up to be emailed as soon as the product is available again. The initial results have been very encouraging.

These email open rates are triple of standard marketing emails, and we’ve been able to recover several hundred thousand dollars of sales in just a few months that would have otherwise been lost. We also are able to capture trending demand data and share that information with the retailers’ merchandising and buying teams.

 

pareto intelligence chicago tech company
image via pareto intelligence

Pareto Intelligence uses data analytics to help health plans, healthcare providers and other healthcare companies discover inefficiencies and improve financial performance. According to George Asante, chief solutions architect, the company keeps a close eye on how users engage with the platform to come up with better ways to serve their needs.

 

How does your team incorporate data into its decisions?

Pareto delivers solutions through an online analytics platform that allows us to gather a tremendous amount of data and trends. There are three main sources we look at: The first is usage trends. We identify which dashboards, reports, alerts and recommendations that our customers use most frequently, as well as the data elements they click through and drill down into. Second, on a periodic basis, we formulate questionnaires based on industry trends and solicit feedback from our customers.

Finally, our data scientists use a combination of client transaction data, usage trends, survey feedback, government regulation and industry trends to give us the quantitative data we need to make better, more informed decisions and improve our services and solutions.

 

Can you highlight one particular data-driven decision that has really helped your company grow?

Analyzing big data collected monthly from our clients has allowed us to better serve our customers in terms of user experience, as well as provide a broader product portfolio, because we are able to proactively identify business problems that our clients will need to solve and design solutions to meet those needs.

 

strong analytics chicago tech company
image via strong analytics

Strong Analytics is literally all about data. The Chicago-based consulting startup works with companies to solve business challenges and develop new infrastructure and processes for analytics-driven decisionmaking. To co-founder Brock Ferguson, the most important step toward becoming more data-driven is to make critical information as accessible as possible.

 

How does your team incorporate data into its decisions?

One thing we see with a lot of our clients, both big and small, is that data is only effectively used in the decision-making progress when they have the right infrastructure in place. If it takes a lot of time to gather the data or to analyze it, decision-makers shift more to intuition — and bad decisions become more prevalent. But with the right dashboards and analytical tools, the friction disappears and organizations can truly become data-driven. The right infrastructure is often a rigorous data pipeline, data warehouse and interactive dashboard. In cases where organizations have analysts who want to dive deeper, we've also created analytical tools like data science libraries for Python and R.

 

Can you highlight one particular data-driven decision that has really helped your company grow?

Although we work in lots of different areas, one major theme in our work is helping clients make better data-driven decisions around marketing. Many companies today still market to a handful of “personas” that they believe exist in their customer base. We help companies measure the kinds of behavioral and demographic data that lets them market to real and diverse customer segments in a much more effective way. We’ve seen massive boosts to customer engagement and revenue simply by tailoring the right messaging to the right people.

 

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