How to Add AI into the B2B Ecommerce Mix

In April of 2017 Forrester released a report predicting a 300% growth in investments this year for artificial intelligence (AI) compared to 2016. This explosion of interest in insight-based marketing isn’t confined to B2C ecommerce either. Other studies report that more than 60% of business buyers expect that suppliers will use AI in the near future to automatically anticipate their needs.

The returns for AI and data-driven marketing are obvious when selling directly to a consumer. Although AI is influencing B2B commerce as well, the benefits are not as directly translatable. AI accelerates returns for B2B organizations in terms of personalization, next generation search, retargeting and reordering, for example, but not in the same way.  Understanding these important differences between the goals of a B2B buyer and those of a consumer can make incorporating AI into the B2B ecosystem much more successful.

In B2B commerce there are many different roles involved in every transaction. Often, the person ordering the goods or services is not the actual buyer, but a procurement specialist. Orders are customized for the unique needs of a specific client, or even a specific contract. Salespeople are involved at different steps in the process, depending on the organization, the industry, and the online maturity of the buyer and seller.

I see several ways AI will drive significant value in the near future for B2B commerce as a whole:

Next generation search including image recognition and text to speech.

Within B2B commerce, efficiency is not only a critical success factor, it’s a primary goal. Manufacturers and distributors often carry custom catalogs containing thousands of items, so the ability to search quickly and effectively for information is vital. Image recognition search embedded within a native mobile app gives the user the ability to launch an image-based search using a photo taken with their phone instead of typing out a search string. Imagine a field repair technician in front of a furnace for the first time. Using their smartphone, they simply snap a picture of the part needing a replacement. Immediately the app returns 6-10 results based on that technician’s contracts, catalogs, and the furnace type.

Text to speech is also of growing interest in B2B ecommerce. Tools like Siri already provide some native capability, but services like Amazon Polly have a capacity for deep learning that can provide huge benefits for B2B commerce.  These AI-based search methods are not mutually exclusive either. B2B sellers offering a suite of options in terms of traditional search, image recognition, and text to speech can accommodate different user preferences. Artificial Intelligence helps us customize the experience to meet the individual, complex and varied needs of personnel involved in each B2B transaction.

Suggestive selling in terms of both reordering and add-on products and services

As the B2B buying process adopts more self-service characteristics, companies are expected to anticipate the needs of their buyers. AI can learn the buying habits of customers, anticipate reorders, and market to those needs well in advance. As B2B buyers become more price-sensitive due to transparency, an AI capability embedded within the promotion component of a B2B commerce system can be trained to predict needs, increasing efficiency and loyalty as well.

AI can also help sell add-on products.  B2B goods and services are part of a complex world where rarely anything is purchased as a standalone item. Warranties, supplemental parts, and technical support contracts, for example, represent additional revenue that can be also be suggested at the time of the sale or even earlier. AI can discern the patterns of common types of orders, and provide suggestions for additional anticipated items or services.

Using real time data to automatically restock and replenish

Within B2B commerce, there is a vast amount of work that goes into ordering the same items, over and over again. From annual contracts, to procurement processes, and even government regulations in some cases, the “rules” that apply to each of these individual orders can be complicated. Artificial Intelligence promises huge advancements in efficiency simply by learning the order history and usage of a customer.  The capacity for saving time and effort by using AI to help auto replenish stock, and perform other physical inventory-based tasks is enormous.

We’re all still learning what “in the moment” B2B commerce will look like but it’s definitely going to become the standard in the very near future.  Predictive types of ordering and other processes based on behavior-driven patterns culled from data will drive not only efficiency, but customer loyalty and of course sales

In the past, AI was limited to larger B2B companies that could afford IBM Watson-type computer capability. But the cloud, with services from Amazon, Microsoft, Google and others, is making AI accessible and affordable for small to medium-sized firms as well. The potential is enormous. We just need to make sure we’re not trying to apply a cookie cutter B2C approach, to a much more complex B2B commerce ecosystem.

Chad Caswell is the VP of Technology and Operations for Insite Software

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