AI: The Unique Role of Apps in Driving Adoption
To say artificial intelligence (AI) is generating a lot of buzz these days would be a massive understatement. According to a recent report, the potential impact of Generative AI on the global eCommerce sector is set at almost $6 Trillion.
The value of OpenAI, the company behind ChatGPT, has been put at $80 Billion, a number that has tripled in the last 6 months. AI is now filtering into all of the breakout sessions and keynote speaker slots at eCommerce trade shows across the US. Artificial Intelligence is hot and getting hotter.
While most can understand the implications of using generative AI to write a term paper or personalize a textual product description to match the demographics of the viewer, few are talking about apps as a key driver for AI adoption in eCommerce.
Chatbots are popular right now (and this field seems to be AI-saturated already), but AI as a tool for driving more app-based eCommerce conversions is where we will see the real value of this powerful new tool manifested. In fact, according to a recent study, 84% of eCommerce businesses say they are either actively working AI solutions into their business or have branded AI as a top priority for 2024.
In order to understand how commerce-enabled apps will play a role in the adoption of AI, one first needs to understand the three ingredients it takes to utilize this new technology in an effective manner. Quickly speaking, they are: 1) a lot of data, 2) data modeling (the “rules” for how this data is used) and 3) machine learning/computing power.
Assuming you have access to 2 and 3 (data models (many are free) and the computing power), the data becomes the crucial fuel for the AI engine – the determinate element that allows AI to function. And apps are uniquely well-suited to capture this data.
Browser-based traffic to a mobile or desktop site is anonymous by design, all the way up to the optional login step – a step that typically only happens at THE END of the use flow, in conjunction with checkout. A 2022 survey by Capterra found that 43% of online shoppers do not login when even given the option, preferring to use anonymous guest checkout instead.
Apps, on the other hand, are inherently personalized. The log-in happens at THE START of the customer journey. Commerce-enabled apps are like a trusted data repository, held literally in the hands of individual shoppers.
Apps allow the customer-centric product discovery process to work, because their very use is infused with the inherent opt-in permission needed to gather the data needed for a more-personalized shopping experience. This is why most people use (and trust) the Amazon app, even though Amazon offers a perfectly good mobile site. Because of this, Amazon is already using AI-powered recommendations to make the personalized product suggestions that drive a reported 35% of their annual sales.
Another example of how apps can play a role in powering AI is loyalty programs. They log actual purchase data to accrue points and often are linked across to brick and mortar in-store purchases. This is exactly the sort of real-world, real-purchase data that allows AI to shine.
After all, the best measurement of intent to buy and consumer preference is the actual, tracked transactions they have made. If a shopper opens an app on their phone and the eCommerce platform knows this person has purchased multiple men’s shirts in XL, the odds are high that the customer interacting with the app is a man with a shirt size of XL. If a female app user always uses their app to buy light beer for in-store pick-up, odds are higher that they will act upon a special offer for a light lager, versus a juicy, heavy IPA.
And not all this data needs to be extrapolated. Apps can simply ASK the shopper to create a preference profile, in order to better surface a more-personalized experience. This personalization used to be considered “creepy”, but no longer. A recent Salesforce study found that almost two-thirds (62%) of shoppers are OK with companies sending them personalized offers/discounts based on items they have purchased in the past.
The same survey of 7000 consumers found that 57% will share personal data in exchange for personalized offers or discounts, 52% would share personal data in exchange for better product recommendations, and 53% would willingly provide their personal information and preferences in return for a more-personalized shopping experience.
While AI can be confusing and intimidating, the myth that it needs to cost an arm and a leg should be dispelled. The computing power and related costs to run monster programs like ChatGPT is indeed expensive (about $700k/day), but AI can be infused into already-existing SaaS offerings, at a relative low cost. In fact many companies, including Unbound, are layering in AI as an enhancement, or using it to sell an already-existing eCommerce option.
Providing a better experience is fine, but converting that to additional sales is where the rubber meets the road and how the bills get paid. Perhaps more importantly, it can also make a hero out of the decision maker who decided to implement an AI layer into an app, so that machine learning can do its thing. Apps are excellent at tracking conversion rates and linking sales to a specific customer. And these customers tend to be the cream of the crop – the most brand loyal, as evidenced by the fact that they downloaded the app.
Discovery or, specifically, the surfacing of relevant product suggestions is the key to having a shopping experience that feels tailored to your specific wants and needs. AI, if powered by data already accessed by app, can fuel this hyper-personalization. Smart online retailers are already taking advantage.
October 31, 2023 Wilson Kerr – President Business Development & Sales