AI’s market size has nearly doubled in the last two years alone, and its growth is showing no signs of stopping. The expectations of customers have been shaped by machine learning and AI algorithms that make finding what they need easier than ever.

Author Nick Saraev

Photo: Freepik

B2B manufacturers need to keep up with these changes if they want to avoid customers leaving their E-commerce platforms unsatisfied. However, there are quite a few challenges that are specific to the B2B aftermarket world. 

Sergio Lacobucci, the senior director of E-commerce marketing with Coveo,  recently spoke at the Spare Parts Virtual Academy about the challenges facing B2B companies moving online. He outlined how the complexities involved with spare parts sales in the digital age can be parsed by AI, if companies know how to use it. 

Common B2B Spare Parts Challenges 

There are several challenges that pop up across the board when companies try to implement E-commerce for their B2B aftermarket sales. 


Customers have high expectations when it comes to the customer experience on B2B e-commerce platforms. They have become accustomed to the B2C model of e-commerce, with one-button purchases and instant, easy searches for information. 

What’s more, as your user base becomes more familiar with the benefits of machine learning and AI, they start to expect that level of personalization across all platforms. If someone uses Spotify or Netflix regularly, they have become accustomed to algorithms that customize everything from the home screen to the recommended media. 

There are a lot of advancements that need to be made in the B2B e-commerce sphere before this bar can be met. 


Complexity is everywhere in B2B, especially when it comes to spare parts. Not only are there massive amounts of data coming in and complex structures to organize it, but that data then needs to be linked to certain KPIs. 

The complexity must be understood because any tech you’re utilizing needs context. If you implement a solution that can’t handle this level of data, you’re going to have countless issues down the road. 

This issue is rampant in the B2B industry, with companies shackled to the technology they’re using, unable to bring the experience to the next level. A solution to this issue is to use a composable approach that grows with the needs of the business. 


As the pandemic forced so many B2B companies to jump to E-commerce quickly, there is still some disconnect between the sales teams and E-commerce platforms. With the sheer size of transactions in B2B sales, this confusion around the process can cause quite a bit of anxiety. 

Customer Experience Expectations

It’s clear that customer expectations are changing, but how? As soon as AI became cost-effective enough to bring into the customer experience space, there’s been a big shift in what consumers are experiencing. This changes the bar of what they think is exceptional, and even acceptable. 

These expectations include 

  • Personalized Conversations – With the ubiquity of chatbots, customers don’t want a series of links to sift through, they want to be spoken to and given a specific answer
  • Prescriptive Experiences – Customers expect you to know what they’re trying to do and give them a frictionless transition from one stage to the next
  • Coherent Journeys – Customers expect to have the same experience with you no matter what channel they’re on. If they phone, email, or check out your website, they want the person they’re speaking with to know who they are and what they’re trying to do 

In order to meet and exceed these expectations, companies need to invest in a few key features on their E-commerce site. 

Good Filters

Customers need to be able to search for products and filter by anything, including stock, price, and more. They should also be able to eliminate any products that won’t fit with the machinery that needs parts. 

For example, if I need new rims for my truck tires, I’ll want to filter my results by my truck make and model, and find out what rims are available in my budget and what my local dealer has in stock. 

Predictive Search

While typing in the search bar, your users expect to see predictive fill like they get on search engines. This can be taken a step further by having suggested products pop up as they search. 

Having this in place allows folks to find what they’re looking for without even having to visit the listing page. The more you can tailor these results to the things they’ve been doing during the current session, the more personal it will feel. 

Complexity Everywhere

If you want to deal with the complexity of the customer experience and business outcome needs while leaving room to scale without breaking the bank, AI is a must. 

There’s an extremely high volume and variety of data points that need to be held and processed to make B2B E-commerce run smoothly. This includes multiple sources of data, millions of documents, hundreds of thousands of products, and catalogs for every price entitlement.

This data needs to be communicated to a large and diversified audience. Both internal and external users will be sifting through it, they might have different cultural expectations, and will likely demand a level of personalization.

In order to reach your KPIs and find success, you need to ensure that the system you’re using can deal with this complex data and make it actionable for customers and employees.

Changing Longstanding Processes

The ideal system for any E-commerce platform will include both an empowered sales team and an empowered customer base. They should be able to access the same information to prevent confusion and be able to search for anything they need with AI. 

This process is achievable, so long as the technology they’re using is compatible with it. As B2B businesses adopt this hybrid model, they have been able to outperform their competitors dramatically. Hybrid sales drive 50% more revenue and help facilitate larger sales. 

When these systems work in harmony, companies can ensure the entire sales process is efficient and effective. 

The Future of B2B Spare Parts and Gen AI

Generative AI is everywhere, but many companies are starting to implement it without fully understanding what it’s capable of. This raises many issues because AI is 

  • Expensive – If AI is engineered incorrectly, it can cost up to 100 times more than a properly applied system. However, getting it right takes a large team of experts. In order to get a good return on investment, teams need to ensure they are using AI for the right applications
  • Reliant on Training – You need to ensure that the data index your AI uses is fresh, recent, and relevant. Even if a document was updated this morning, you need to be sure that the right people gave access to it right away

The ultimate goal of generative AI is for customers to be able to get as far as possible with self-serving. They should be able to ask questions and get answers based on all the content that your business already has. This can take sales calls down from 45 minutes to 10. 


The use of AI in B2B E-commerce is essential for manufacturers to stay competitive in the marketplace. With the rapid growth of AI and machine learning technology, customers have come to expect a personalized and efficient experience when purchasing parts and products online.

However, there are unique challenges in the B2B aftermarket world that AI can help solve. By understanding and utilizing AI effectively, B2B companies can improve their spare parts sales and provide a better overall customer experience.

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