Why B2B Brands Still Struggle With B2C Experiences

In today’s competitive online landscape, providing a seamless buying experience is crucial for the success of any company, whether it operates in the B2B or B2C realm. However, B2B brands often face unique challenges that make it difficult for them to meet the level of customer experience that their B2C counterparts are able to deliver.

It goes beyond just a UX challenge; the complexities of the B2B buying journey require sophisticated search and browse technology that exceed basic recall and can provide relevant products, rich information, and pricing that match the unique needs of B2B buyers. In this article, I’ll explore the reasons B2B brands struggle to meet B2C experiences and how they can overcome these challenges to optimize the buying experience.

The search challenge for B2B buyers

One of the primary challenges that B2B companies face revolves around search and discovery. Many B2B ecommerce platforms still provide rudimentary search experiences, lacking the robust capabilities needed to meet the demands of B2B buyers. A B2B customer performs significantly more interactions and interaction types than a B2C customer would. Particularly for new purchases, B2B customers perform significantly more product and supplier research in advance of purchase than a B2C customer does. Providing the buyer with all the functionality to support the myriad of interaction types is important to drive purchases and reuse of your channel.

For example, a significant amount of B2B transactions are simple part, component, or replenishment purchases. Providing a quick predictive part lookup, reorder based on past purchases, recommenders for compatible accessories and triggers for support, maintenance or upgrades can go a long way to drive your repurchase rate and overall customer lifetime value. B2B companies also deal with complex products that require rich and informative content to aid in the buyer’s decision process. Providing an information-rich experience that surfaces all relevant information goes a long way to drive credibility and confidence in the supplier.

Bear in mind B2B workflows

Multi-stage, long duration purchasing workflows such as the below are common in B2B commerce. Presenting the relevant result types based on where the buyer is within this journey is a common challenge. Machine learning models can predict where the buyer is at based on their behavioral patterns using semantic extraction of keywords and intent extraction based on their clickstream.

Where large language models could come in

Employing a large language model (LLM) such as the popular Open AI GPT or Google PaLM can be used to perform a deeper level of extraction across documents and products to help uncover content and journey-intent relationships. Based on that, the most appropriate types of results and content can be shown to the user reducing bounce and increasing the likelihood of purchase. Common result types that appear across a B2B purchase journey may include informational video, blogs, community boards, FAQ’s, social proof (ex. Reviews, usage images), spec sheets, chatbots, configurators for custom products and eventually the final product itself.

Accuracy and error reduction take priority

Reducing purchase errors is another major factor to consider in B2B, particularly due to the generally higher volume and cost per order compared to B2C. Compatibility such as fitment to a specific machine, providing accurate configurator options, and product fit within defined constraints can be critical. Not to be forgotten is real time and accurate pricing, availability and fulfillment data. Given the significant volumes and mission critical nature of B2B purchases, it is critical to eliminate any latency in availability and lead time of products.

Leveraging general industry standards databases such as those from ANSI (American National Standards Institute) that match to your target buyer’s industry can help both in understanding the buyer’s terminology as well as core product requirements. Industry specific codes such as Aftermarket Catalog Exchange (ACES) and Product Information Exchange Standard (PIES) are examples of standards used in the automotive aftermarket parts industry. Incorporating local building or other compliance codes into your data can be another approach to reduce purchase errors and simplify the purchase process if your buyer’s industry is in construction. Here LLM based technologies can be of great use as they could incorporate the corpus of these standards into their generated results.

As the global market continues to expand, B2B companies need to be able to translate this complex content, from product descriptions to material safety data sheets, into different languages. Unfortunately, many SaaS search platforms are ill-equipped to handle these requirements, particularly searching across content and product in multiple languages, leaving B2B brands struggling to deliver the necessary level of information and multilingual support. Leveraging a platform that can process and understand content in the major languages as well as cross-language support is a major way to grow customers and revenue globally. Machine learning based translation and speech to text, and LLMs are technologies that can be employed where your text has not yet been translated.

The custom catalog and product alias challenge

A common catalog scenario in B2B is that each customer may have both their own catalog of products and access to a shared set of products. This shared catalog set will often have multiple identifiers associated with them, such as the manufacturer’s identifier, the distributor’s identifier, a customer specific identifier or the industry-standard code. Some will even have different attributes and values for the same product. The technology used by B2B platforms must be capable of supporting this logic at scale, and dynamically discriminate between different types of numeric searches. Moreover, it should provide relevant alternatives when a particular product is unavailable, enhancing the overall user experience.

Real-time updates are another critical feature that B2B platforms should prioritize. By updating product availability in real-time, B2B companies can gain significant business advantages, particularly in the face of increasingly common supply chain disruptions. The ability to provide accurate and up-to-date information about product availability helps build trust with customers and enables them to make informed purchasing decisions.

Conversational B2B Sales and Service

Chatbots and messengers have been prevalent primarily in sales assist which is limited to the catalog and content data the agent or bot has access to, and customer service use cases which are limited to information in knowledge management and CRM repositories. That creates a great deal of frustration for the buyer. Thanks to the power and depth of LLM’s, the data the agent or bot has access to becomes virtually unlimited. They now have global access to an essentially local knowledge base. They also now have a co-pilot to generate a meaningful guided sales conversation with a buyer or troubleshooting dialogue for a service request which will drastically improve productivity and customer satisfaction. This will also undoubtedly allow b2b companies to scale tremendously, regardless if their direction is an automated conversational experience or an ai-assisted one.

Where to start

Implementing these improvements doesn’t necessarily require B2B companies to undergo an expensive re-platforming project. Even if they are operating on older platforms, they can still enhance their B2B ecommerce experiences and personalize shopping by partnering with search platform providers.

One example of this is the partnership between Lucidworks and one of the world’s largest B2B technology providers, which resulted in impressive results. By modernizing its product discovery system, the company experienced a 10% increase in add-to-cart, a 40% decrease in zero-results search, and a 3% increase in conversions. This success story highlights the potential impact of implementing the right technology and solutions to improve the B2B buying experience.

B2B brands face unique challenges in meeting the level of customer experience provided by their B2C counterparts. However, by focusing on enhancing search and discovery capabilities, incorporating important product and content discovery features, and leveraging real-time updates, B2B companies can bridge the gap and optimize the buying experience for their customers.

At Lucidworks, we believe search is key to unlocking meaningful experiences that delight users and customers. Learn more about how we can deliver the B2C experience your B2B buyers deserve. Contact us today.