Hindsight : July 2024

Thrilled to welcome the distinguished Howard Tullman on this episode of Unqork’d & Unscripted. Howard is known for his multifaceted roles as a founding Executive Director, educator, and venture investor. He established the Ed Kaplan Family Institute for Innovation and Tech Entrepreneurship at the Illinois Institute of Technology, emphasizing his leadership in fostering innovation. As General Managing Partner of Chicago High Tech Investment Partners, LLC and G2T3V, LLC, he drives early-stage investments, demonstrating his commitment to nurturing tech startups.

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Howard’s influence extends through board memberships in numerous tech companies, leveraging his expertise as a technology advisor and business leader. Join us today at 1:15PM ET as Howard shares his insights on his impressive journey and knack for emerging technologies.

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Take Control of Your Company's Data-- Or AI Will.

The vast amounts of data that your company is now producing is the raw material of AI. You need to learn how to harness it to create better experiences for your customers. Focus on these four key areas.

EXPERT OPINION BY HOWARD TULLMAN, GENERAL MANAGING PARTNER, G2T3V AND CHICAGO HIGH TECH INVESTORS @HOWARDTULLMAN1

JUL 2, 2024

It seems that 200% of the conversations that I'm having with the teams running our portfolio companies, as well as those with other entrepreneurs across a dozen different industries, are about chatbots, the dominance of the primary large language models (LLMs,) and the unlikely prospects of the other emerging AI tools and models. Very few of these discussions are focused on the much more pressing and immediate concern: who's creating, who's aggregating, who's vetting, and who owns the masses of underlying data that every business is now generating daily? Further, how is all of this material going to be used to move those businesses forward, and by whom?

The excessive focus on the AI "engines" seems somewhat misplaced because it's the data that's the fuel-- the source material, the content if you will-- which ultimately drives these AI machines and determines the accuracy, quality and value of their outputs. Every business is going to need to develop its own data guidelines and monetization strategies, if any, and they'll need to decide how they will use their accumulated data to improve and extend their internal operations. Growing their customer attachment, loyalty and engagement and improving the overall experiences of their users and clients will be one of the most important data applications for the next several years. And because few of these new firms have the requisite AI talent and skill sets already onboard, figuring out how to employ the wealth of new digital information now at their fingertips isn't going to be easy.

We've already learned that these kinds of questions and concerns aren't as simple a matter as "garbage in, garbage out" because the machines themselves have already learned to optimize their responses for believability over accuracy. That's because humans, being the lazy and Pollyannish folks that we are, clearly prefer some answer-- in fact, any answer-- rather than a system that responds with a goose egg or "I don't know." The tech bros immediately started calling the LLMs programmatic tendencies to output lies, fake statistics, and made-up fabrications by the anodyne term "hallucinations," highlighting the fact that we're already losing control of these systems and the ability to determine what is real and true in many cases. Sadly, the developers have done a great job of simplifying the output and a terrible job of providing audit trails, references, or other checks and balances describing how the output and conclusions were reached and what specific information they were based upon.

An even bigger question will be whether and how these data-rich firms will share their information and results with third parties while protecting the privacy and confidentiality of their own users, customers, clients and partners. The exponential and voracious demand of the LLMs for more and more content means that almost every company will be approached and solicited to sell its data to users, brokers and other aggregators. These financially appealing pitches will be especially attractive to startups, because the vast majority of new businesses have their hands full running their own shops, can always use additional cash for little effort, and simply don't have the resources, people or time to develop and deliver solutions that can economically market their own data to others.

But selling off their data is likely to be a serious mistake in the long run. Even if they can't do it all or even do it very well at the moment, successful businesses will need to commit to figuring out how to use their own data to drive and enhance their operations. Because the big winners of tomorrow will be those data-driven businesses that are focused on two key objectives: (a) learning as much as possible about each and every customer and prospect and (b) using those findings to accurately predict and ultimately favorably alter the behavior of these individuals to drive improved financial performance.

Every company can start down this road to greater enlightenment by understanding that-- specifically in the eyes of the consumer-- there are pretty clear lines between proper and improper uses of customer data, even apart from any legal requirements. Most of us long ago made a series of decisions and trades where we largely gave up on transactional (as opposed to personal) privacy in the interests of ease of access, convenience, and saving time. As a practical matter, this means that, so long as businesses stay within four basic guardrails, we're more than willing to have data about our behavior and activities in their possession used to make our daily digital lives and our dealings with them easier and simpler.

The four key areas of permissible data use are also the key elements for any company's comprehensive data management plan. And while they may ultimately be accelerated, streamlined and strengthened by the processing, analytical and predicative capabilities of AI, the fact is that the foundations for each component already exist in many firms and can be developed and utilized in a less technical and complicated fashion right now. The main requirement is to get focused and get started. The four areas are:

(1) Speed and Ease of Access and Use

This is probably the easiest and most obvious area where customer information management systems can be used to speed the selection and shopping process, eliminate redundant actions, supply prior information and apply preferences, accelerate payments, and offer alternative delivery options. No one is unhappy about having their time saved and their patience salved and only prudes care about their "privacy" when they're just trying to get something done and done right as quickly as possible.

(2) Service and Support for Customers, Products and Services

As hard as it is to sometimes believe, millions of businesses treat their returning clients and customers as strangers, newbies or random visitors rather than immediately acknowledging their prior connections, service history, and product or service needs. On the other hand, we're also seeing more and more instances of proactive service alerts and interventions (smart washing machines come to mind) so that problems, interruptions in use and service, and other issues can be resolved before they arise-- and often even behind the scenes without any involvement from the user. Here again, no news is the best news if it means I don't have to worry about something abruptly breaking down in my home or office.

(3) Suggestions, Bundles, Subscriptions and Sales

Anyone who has made multiple trips to the store or a website because you forgot certain simple but critical items quickly comes to appreciate smart systems, which do some modest suggestive selling, remind you unobtrusively about packages, bundles, recurring purchase discounts, and related purchases; or the cables and other pieces necessary to operate and enjoy your new gizmos. Some firms, like Amazon, do this far better than others in large part because Amazon knows what you have recently purchased and doesn't waste your time or its opportunities offering you a chance over and over again to buy the same item you selected three days ago and won't need to restock for another six months.

(4) Surveys and Satisfaction Measurement and Management

Some things never change. Happy customers may tell a friend or two about a successful purchase or service experience; unhappy customers badmouth your business all over town. This is why customer service and satisfaction management programs are absolutely essential but also must be executed with care and in a manner that isn't unduly intrusive. This is just as difficult as it sounds, but the best organizations make it their business to actively and promptly ask their customers for feedback and to act on the information they receive. Getting a survey in the mail 90 days after you visit some car dealer or have your vehicle serviced is a waste of everyone's time. Real time inquiries and responses make an important impression on customers and clients, demonstrate a sincere interest in them individually (assuming it's not some pro forma phone call from a call center in a distant place) and absolutely lead to additional customer engagement and revenue.

Bottom line: you don't need a magical machine or some new AI genius to start using your wealth of data to do a better and more comprehensive job of serving and supporting your customers. Rather than being offended by the fact that you know something relevant about them and their connection with your firm, they'll be the first to say that they're grateful that you aren't wasting their time.