According to Shawn Cope and Kathleen Lewarchick, the director of front-end engineering and vice president of marketing at Xngage, predictive “machine customer” buying behavior is much farther ahead than you might imagine.

Shawn Cope, Xngage

Shawn Cope

In Part 2 of our Machine Customers series, we further expand on the emerging $30 trillion business-to-AI (B2A) marketplace. In Part 1, “The coming era of machine customers,” we introduce the concept of a custobot, a “non-human economic actor who obtains goods or services in exchange for payment” (Gartner.) We shared an example of how it could work in practice, and in this second part, we discuss  the technological underpinnings in greater detail.

If the Bill of Materials (BOM) is programmed into a smart machine, the custobot can search on any of the keywords or specifications.
Kathleen Leigh Lewarchick_Xngage

Kathleen Lewarchick

Since the decision-making around integrated machines is usually complex, we start with a typical custobot journey map. By capturing its flow, people can gain more clarity around their own roles of ownership, responsibility, IP, and security. And the journey really begins in just the first few seconds — dare we say nanoseconds? — within a transactional ecommerce environment.

The First Seconds of Your Machine Bot’s Journey

The first action step in a custobot’s journey is to identify a product need. The machine might do this through a regulated chip or sensor that provides data: examples include usage level, power level, or variations in tolerances. A data point (or need) drives a purchase occasion. You can see how a car wash soap machine (out of suds,) or a battery-powered system (out of juice,) might know when it’s time to reorder. But conditions requiring tight tolerances might be harder to manage, especially in cases where holiday seasonality or weather conditions may come to bear. And yet, predictive “machine customer” buying behavior is much farther ahead than you might imagine. Some vending soft drink machines have built-in thermometers, for example, to assess heat conditions (and pricing).


Once the need is identified, the custobot can use machine-learning and artificial intelligence to conduct a smart search. If the Bill of Materials (BOM) is programmed into a smart machine, the custobot can search on any of the keywords or specifications. If an item was previously searched, reviewed, or considered (through authentication,) that history might also be added to the query.

Once matches are found, the custobot can use pre-determined filters (like budgets, specs, brands) to then evaluate the shortlist of options for consideration. A custobot might know, for example, that there are two acceptable lightbulbs for its smart lamp. Because of the variability of pricing, shipping terms, delivery windows, and taxes, the distributor who gets the buy box or order will likely have the best real-time information and the most positive credentials, such as ratings-and-reviews.

The operative word in all of this is “smart.” Now is a good time to take measure of your ecosystem to determine where you are already ahead, and what obstacles you might have to navigate, in your platforms (ERPs, PIMs, DAMs) and other systems.

What to Do Next – Engaging Your Technical Experts

Data Preparation

On most B2B sites the current level of data is often quite sparse. Custobots will make purchasing decisions based primarily on information systems rather than personal relationships and will place a heavy emphasis on comparing a product’s attributes. This means you must vastly expand on the amount of detail available for a product’s specifications and attributes.


It also means that a strong push should be made towards standardized product attributes — now, while there is still runway left. According to Wes Smith, the President/CEO of the National Association of Electrical Distributors (NAED), through the IDEA’s data synchronization services, “the electrical industry continues to advance its product standardization effort, focusing on a goal of harmonized industry data that is consistent, compatible, and complete.”  IDEA is the Industry Data Exchange Association and is jointly owned by NAED and the National Electrical Manufacturers Association (NEMA).

Why standardize? Because it benefits every participant in the customer journey and will do so for machine customers one day.

Streamlined Products and Pricing with Optional Authentication

Common to B2B websites is the practice of locking catalogues behind an authentication wall. This could shut out guest purchases and present a roadblock to acquiring new customers. However, when a custobot encounters a digital store front as either a guest or authenticated user and it finds limited or no products, a website may rank lower in algorithms, resulting in lost opportunities.

Similarly, in B2B, pricing for a particular product is negotiated per customer or contract, and the price is hidden behind authentication. This pricing method simply won’t work for a custobot that wants to purchase and must at least have an opening price point for comparison. While there is merit in having a better price for volume customers, standard advertised prices are needed at the very least so you don’t risk losing easy sales and lowering your preference rankings in algorithms.


Influencing the Industry Standards

Start Search Engine Optimization (SEO) now to influence the artificial intelligence (AI) models that future machine customers will leverage. If models think specific attributes (e.g., “fit” or “material”) are the most important factors in a buying decision and your products score well there, you will likely win customers based on this foundational groundwork. Large language models are known to have some inherent bias and setting authority for search terms is an important first-mover advantage in the world of machine customers.

In Summary

The coming world of machine customers is already well underway. Setting a place at the table for your new customer requires smart planning and preparation. Since digital moves quickly, start by gathering a cross-departmental, cross-functional team and identifying what people know and don’t know about machine customers. This team can then identify gaps in a custobot customer journey, and then work with subject matter experts to assess the feasibility of solutions.

Pairing Product Management with IT resources will help uncover roadblocks to data flow and create the right single source of truth for product and pricing management. Pairing Marketing and IT resources will help uncover roadblocks to the golden order through API and SEO management. At the very least, by this time next year, everyone in your organization should know what machine customers are and why the company’s digital and IT investments will continue to grow.

Say hello to the new face of customers.


About the authors:

Shawn Cope is the Director of Front-End Engineering for Xngage LLC, a B2B digital commerce services company with more than 60 clients across the industrial trades. Throughout his career he has cultivated a passion for bleeding-edge technologies and crafting user experiences.
Kathleen Leigh Lewarchick
 is the VP of Marketing for Xngage. She is the former PURELL® Hand Sanitizer Brand Director, has co-created automated replenishment products with Amazon Business, and created telehealth solutions for a company that she later helped sell to CVS Health. 

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