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Utility Buying Experience
Buy everything you can, not everything you need.
The Utility Buying Experience delivers a Buyer-Wins Outcome by using the Information Buying Experience to enable the Buyer to do two things.
First, identify a Clearly Superior Alternative to their problem with minimal Botheration And second, to purchase it; both from a single source.
And containing the 7 elements of the Information Buying Experience: Accelerated Cognition, Relevance, Free-will, Clarity, Learning-centric, Option-rich, and Trust.
Flip a switch, find what you need, qualify its value, place your order within two hours for same day delivery. Twenty-eight percent of Amazon purchases start and finish in under three minutes. The cost of getting the expertise needed to buy the best solution to the problem is near zero, so the Buyer buys everything they can through it.
The depth of solution expertise curated for the Buyers problem is the limitation of the Utility Buying Experience. Artificial intelligence is a long way off from being able to deliver curated expertise for complex problems and the Buyer's complex queries.
And this is why the Buyer still very much needs the Expert Seller.
Utility Buying Experience Demand
Years of buying what they need through the Utility Buying Experience has conditioned Buyers. No Digital Seller has a chance of competing with the Amazon experience, unless they offer something so unique and desired that the Buyer is willing to forgo that experience. But they know they're getting a sub par experience and they don’t like it. The Buyer expects to receive the Utility Buying Experience. It has become the standard, normal. When it isn't offered, its weird. In an Instant Buyer Response Loop, Buyers follow the Click Off Response to find it elsewhere.
Complexity Curve
As the sophistication of the expertise needed to be curated for the Buyer's problem increases, the ability for the Utility Buying Experience to supply that curation decreases. The relatively static nature of the information provided limits the curation capability available. So while curation to a certain degree exists in the Utility Buying Experience, particularly with respect to other Buyer's experience with the solution, fully curating expertise is not available. This is why the Buyer buys everything they can from the Utility Buying Experience, but why they can’t buy everything they need.
Query Complexity
Hold on ChatGPT. Query Complexity says that the demands of the problem are too complex for the Buyer to form their own query of it. They cannot account for all the characteristics and unique attributes of the problem itself and all the areas it affects, plus all the myriad particulars of their own operational and business requirements (my current management, my current infrastructure, my current people, my current budget, my current understanding, my current expertise) to form a reliable scope to be inputted into a system, such that the system can generate curation of expertise to meet the Buyer's requirement. Even given the power of Large Language Models like ChatGPT, the bottleneck to use remains in the ability of the Buyer to formulate a query that puts them to work. Expert Sellers remain very much needed by the Buyer.
Bonded Human Accountability Barrier
The Bonded Human Accountability Barrier exists when the Buyer is unwilling to trust their need for Curated Expertise to an artificial intelligence source, with it’s lack of accountability, lack of attribution to sources of the content, and it’s propensity to hallucinate. As the sophistication of the Buyer's need for Curated Expertise rises, and their risk tolerance for making a bad decision decreases, the Buyer has a preference for Curated Expertise from the Expert Seller with their Bonded Human Accountability.
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