Why Your Company Should Even Bother With Data and AI

Every week, I’m in conversation with founders, and the topics of data and artificial intelligence come up again and again. Many of the small business owners I speak to express confusion about what–if anything–they should be doing on those fronts. They’re being bombarded with marketing for data and AI products and services, but they’re not sure what to do with all that information.

What are the real gains your company can achieve by modernizing its approach to data and implementing AI?

As a data scientist, founder, and reporter, I’ve thought a lot about this. And I’ve identified three key areas where companies tend to see real gains:

1. Increase Productivity.

The most immediate way your company can benefit from implementing data and AI is to increase efficiency in tackling certain tasks–particularly repetitive or error-prone human processes where machines can do a better job. A lot of companies have many thousands of rows of important data sitting in Excel spreadsheets or similar. There’s a good chance yours is one of them: Your team brings data into spreadsheets by hand and manipulates it through complicated calculations, deploying valuable human effort to do so. Contrast that to a modern data and AI approach: Your company’s data-whether it is about customer behavior, marketing analysis, inventory management or some other aspect of operations-gets shuttled into a more robust repository, like a database in the cloud. Well-established processes for getting the data properly in place, called ETL (Extract, Transform, and Load) guide the migration.

About a year ago, Eyeful Media, a digital marketing agency in Dallas (No. 542 on the 2021 Inc.5000), began modernizing its data stack. The company used to receive all its client data in spreadsheets, and would keep the data in spreadsheets while performing manipulation and analysis; the spreadsheets consistently crashed during those efforts due to the processing load on their local computers, memory errors, or other typical spreadsheet problems. Not only were Eyeful’s high-salaried analysts spending too much time wrangling data, but they were also constantly dealing with software errors. They were generating reports manually, says CEO Antonella Pisani, “taking away their time to focus on more strategic work.” Since it’s embraced a modern data and AI approach, however, Eyeful now pushes the information it collects from clients into databases, and then uses dashboard tools to automatically generate reports for clients that present easily digestible analyses.

If you can put these processes and structures in place at your own company, you’ll save your team the time it takes to do this work by hand – increasing the efficiency of the process, the accuracy of the resulting data, and-likely- the happiness of your people.

2. Gain Novel Insights.

Tapping into the computing power of the cloud, and leveraging the sophistication of analysis that is possible with databases, Eyeful to deliver far better results to clients than they could with Excel-generated reports. The dashboards built on top of that stack are more convenient, easier to read, and they refresh automatically. When Pisani recounts some of her big wins from the past year, she points to the insights her clients have gained into their marketing efforts from Eyeful’s new breed of reports. Collecting a larger set of data, and crunching it across a wider array of criteria, allows Eyeful “to solve some of the bigger problems these clients are dealing with,” says Pisani. With their new approach, she says, the depth and breadth of their analyzes far outstrips what are used to crash their spreadsheet programs. Where a spreadsheet-based analysis might look at one or two criteria in relation to each other, the new approach can compare and contrast many different types of fields at once. So instead of simply looking at trends for all customers over time, with a modern data stack, it’s a lot easier to cluster customers into various groups and categories in the same analysis, and then break that data down by product areas. Pisani recalls one of her clients telling her, “This is so cool, I would have given up my first-born child for this dashboard.” Luckily, it didn’t come to that.

When you use a modern data stack, not only do you get data that is more secure and calculations that are more reliable than they are in spreadsheets, you create opportunities for greater understanding of your data. It might allow you to develop personas for your customers so you can target them more effectively, or analyze marketing efforts through A/B testing, or learn that a certain product only sells well when some other product is on sale. And it all can be automated to appear directly in dashboards for management–thus freeing your top talent from the task of creating the analyses, and instead giving them the time to make decisions based on the insights.

3. Offer Additional Features in Products and Services.

What your company does today may not seem AI-centric at all. Perhaps you sell physical products, or offer expert consulting services. But once you have a data platform up and running that can deliver insights, you can package those insights to boost sales. For example, AI-based recommendation engines are a common tool that companies from Amazon to Netflix use to increase sales. When customers are purchasing one product or service, your sales platform can recommend related products or services, based on the behavior of other customers.

You can also deliver insights to your customers about themselves, based on similar analyses, turning automatically-generated reports into a product. Think of the year-end reports you receive from music services or credit cards that tell you about your choices as a consumer, and how applying a similar approach within your company’s offerings might look.

Going from insights to new features – or entirely new products – opens a wide range of opportunities, depending on where you start and what you find.

There are many additional reasons to get started with modernizing your data and bringing AI to bear on your current processes. We’ll be getting to more of those over the course of this series.

Do you have questions you’d like to see us answer? If so, just drop them in the form below to let us know.

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