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AI in B2B Ecommerce: Tools for Personalization and CPQ

AI in B2B Ecommerce: Tools for Personalization and CPQ

9 mins Read
AI in B2B Ecommerce: Tools for Personalization and CPQ

Modern B2B buyers seek the same self-service options they enjoy in their personal shopping experiences, even when buying complex products. Yet, many B2B companies still treat their websites more like static catalogs than dynamic sales engines.

 More and more B2B enterprises are leveraging artificial intelligence (AI) to bridge this gap between outdated ways of selling and current customer expectations. Spurred by technological breakthroughs, like the introduction of ChatGPT, AI is no longer just about automating simple tasks or content creation. It’s now a linchpin for delivering personalized experiences that empower sales teams to operate more efficiently. AI is rapidly becoming an indispensable asset in B2B ecommerce, whether it’s enhancing sales strategies through guided selling or streamlining conversations on price with AI-powered configure-price-quote (CPQ) tools like visual configurators.

In this article, we will explore the transformative role of AI in B2B ecommerce, diving into its impact on customer experience, its practical applications in B2B, and why it’s a game-changer for marketers and sales professionals.

The Rise of AI in Ecommerce

While AI has achieved buzzword status in 2023,  it’s been a transformative force in ecommerce for over a decade. With milestones ranging from chatbots to recent innovations like AI-driven content and supply chain optimization, AI has evolved from a nice-to-have to a necessity in today’s B2B ecommerce landscape.

For example, in the area of ecommerce data management, AI has significantly reduced manual labor by automating the ingestion, cleansing, structuring, and enrichment of product information. This streamlines operations and enhances the customer journey through personalized experiences. AI also enables businesses to gather and analyze customer data more effectively, including the use of zero-party data, to better understand and meet consumer needs. This, in turn, boosts engagement, satisfaction, and sales.

Here are some of the major breakthroughs and ways B2B ecommerce stores of all sizes can benefit from AI technology.

Personalization

Ecommerce stores can use AI to tailor the buying experience to individual needs, enhancing satisfaction and confidence. This approach helps ecommerce companies provide guidance and assistance similar to a sales clerk in a brick-and-mortar store.

An advantage of AI personalization is that it can be instantaneous, using machine learning, deep learning, and natural language processing (NLP) to recommend products, services, or content that fit a customer’s exact needs in real-time. 

Personalization allows for improved ad targeting, better customer segmentation, and tailored product recommendations based on specific customer preferences and previous purchases. So customers are more engaged and have a smooth, streamlined shopping experience.

Chatbots and Guided Selling Assistants

Research by Juniper estimates that by the end of 2023 over 70% of chatbots will be retail-based, and chatbots will help drive transactions and sales. AI guided selling assistants and chatbots help consumers find information and answers to their questions in real-time, facilitating a seamless online shopping experience.

These tools also can be used to assist customers through all stages of the customer journey, including providing personalized product recommendations. 

However, the efficacy of chatbots and guided selling assistants can vary. To truly elevate your customer experience, it’s crucial to choose tools that not only fit your brand but also excel in needs-based selling. Zoovu’s AI-driven solutions provide this balance, offering personalized and efficient customer interactions that align perfectly with your business objectives.

Predictive Analytics

AI has the ability to efficiently collect and analyze consumer data, enabling these tools to better understand your customers based on past searches, buying patterns, demographics, and real-time activity.

This type of information can help B2B ecommerce companies gain insights into the consumers, improve communication to better meet customers’ needs, and assist with personalization — allowing for a more friction-less buying experience. Additionally, predictive analytics helps companies anticipate customer needs, behavior, and preferences, allowing them to create an engaging, personalized experience that enhances customer satisfaction and potentially builds loyalty.

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Integrating AI into B2B Ecommerce

As the adage goes, “Garbage in, garbage out.” If your retail business hasn’t optimized its data to fuel digital experiences—be it configurators, guided selling assistants, or content creation through Language Learning Models (LLMs)—your ability to effectively implement and adapt these technologies will be compromised. Zoovu’s platform can help you navigate this by ensuring that your data is structured and enriched to make the most out of AI-driven solutions.

Businesses should always be focusing on driving operational efficiency whilst improving the customer experience and journey. Zoovu does this and more. It’s a no-brainer decision.

– Rajiv Nema, Senior Director, Partner Engagement and Marketing, SAP Store

Here are some key elements to ensure you can integrate AI into your ecommerce business.

Data Cleansing, Structuring, and Enrichment

Inaccurate, outdated, and bad data costs ecommerce businesses money. For instance, the Nielsen Norman Group found that 20% of unsuccessful ecommerce purchases are a result of a lack of product information.

But having comprehensive product descriptions, content, and images isn’t enough; you also need optimized and enriched data to unlock their full potential. This underscores the importance of data cleansing, structuring, and enrichment processes to maximize your ecommerce effectiveness.

For example, data cleansing removes errors and standardizes units for weight, size, temperature, and speed. When combined with data structuring and enrichment, this process enhances product visibility, improves click-through rates, and boosts conversions.

To make the most of your data, you need it to be accurate, complete, consistent, relevant, and up-to-date, which these steps can assist with.

Content Ingestion

AI can also assist you with integrating your content and data, whatever the format or source. This replaces the need for dedicated marketing or product teams to digitize resources manually. Instead, platforms, like Zoovu, automate this process to help mitigate human error. So you increase efficiency, save time, and provide more accurate product data to build brand loyalty.

Cleansing

Having quality product data is essential for a streamlined, efficient ecommerce business, especially for multichannel companies. Data cleansing helps you remove duplicate content that may negatively impact your ranking, identify and monitor inaccurate product information, and update incomplete information.

Data cleansing isn’t a one-time activity but an ongoing process. It helps ensure your data stays up-to-date so customers have access to accurate information to facilitate their buying journey.

Structuring

Your data should be meticulously organized and standardized to enable tools to efficiently search and understand the information. Take customer searches, which often hinge on categories like type, brand, and price. A simple error—like inconsistently labeling the same product type as both “web hosted” and “cloud-based”—can result in inaccurate product recommendations. Similarly,  mixed price formats, such as “$200” and “200 USD,” can compromise the data and ultimately impact the customer experience.

Enrichment

Product data enrichment enhances your raw product data.

Tools also can help translate technical specifications into understandable language customers can use in the context of their needs. You can also use feedback from customers to help identify how to add value to your existing product data.

Structure, cleanse, integrate, and enrich all of your product data at scale

Check out Zoovu’s Semantic Studio

Personalized Buying Experience

As discussed, AI tools use data and automated workflows to help personalize customers’ buying experience.

Providing a personalized experience can build brand loyalty, increase sales, and lead to higher levels of customer satisfaction.

Here are some AI tools that can help adapt and personalize your customers’ ecommerce buying journey.

Guided Selling Assistants

AI-powered guided selling assistants can enhance customer experience and augment the abilities of your best salespeople on your ecommerce site. These tools help customers find the right product using needs-based questions.

For instance, Zoovu’s AI guided selling assistants are fast, seamless, and automate one-to-one engagements — at scale. Customers can communicate what they need and get instant, real-time personalized recommendations, making it easier to find what they want and increasing satisfaction.

Intelligent Search

Customers don’t want to search for products using item numbers and exact product names. Intelligent search makes it easier for customers to find what they need faster using the way they naturally search.

For instance, Zoovu Intelligent search uses natural language processing technology like contextual understanding and semantic search to improve the search process and get information and answers from various sources — without necessarily needing to exactly match the information. It uses natural language technology to identify meaning and make correlations, providing a better customer experience.

Visual Product Configuration

Visual product configurators replace the need of searching through outdated sales spec sheets to determine if a product is compatible. Instead, visual configurators ensure the product bundles, designs, and configurations are all possible through it’s understanding of the connections and dependencies between your product catalog.

For instance, Zoovu’s  visual product configurators are designed to help make the CPQ process simple for new salespeople and ensure there are no mistakes in ordering. They are constrained by preset rules, so only viable configurations can be made based on elements like function, technical aspects, or budget limitations.

How to deliver greater customer experiences for today’s digital-first B2B buyers.
Read the post

Buyer Intelligence

Buyer intelligence provides you insights into your customer, including why they buy, how they make decisions when purchasing and the types of product and content messaging that work. So, you can better understand their priorities and challenges now and in the future.

As a result, companies can create marketing messages and make business decisions that are better informed.

But how do you gather and use data to assist with buyer intelligence? The collection of zero-party Data.

Zero-Party Data

Zero-party data is information customers proactively and intentionally share through discovery experiences, such as through your guided selling assistant. This type of data is considered more trustworthy and definitive compared to other forms of data since you’re getting it directly from the customer.

You can use zero-party data to help your communication with customers and improve personalization, such as guiding them to products or information based on their answers.

AI-Powered CPQ for Ecommerce

Previously, configure-price-quote (CPQ) data has often been stored in different programs, like spreadsheets, email, and even internal knowledge within different teams, making it harder to fully analyze and use the information. 

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AI in ecommerce

Now, advances in AI technology allow CPQ systems and solutions that can help streamline sales operations, simplify and optimize the process of configuring products, identifying pricing, and more.

The AI tools help to automate tasks, increase efficiency, provide a centralized database, visualize trends, and identify recommendations. 

Precision and Accuracy

AI-powered CPQ tools help to reduce human error in configuration and pricing. Additionally, they can reduce the time needed to understand complex catalogs and product suites to help guide customers to the right product.

AI algorithms can also create accurate quotes efficiently even when using customized parameters, making it easier to tailor quotes and information to specific customer needs when necessary.

Dynamic Pricing

Many ecommerce stores no longer rely solely on the supply and demand rule when establishing pricing. Instead, more companies embrace dynamic (or variable) pricing and selling strategies like offering a discount for a specific time.

AI-powered CPQ tools help to gather and analyze data to help companies create and manage their dynamic pricing, increasing sales efficiency and streamlining omnichannel selling. Using AI will help businesses optimize their dynamic pricing algorithms, identify patterns, and enhance efficiency.

Enhanced Customer Experience

AI-powered CPQ tools can help ecommerce companies elevate their customers’ experience through personalized configurations and recommendations based on customer data and predictive analysis.

For instance, shoppers can receive faster responses to inquiries, especially regarding customized quotes and pricing. Quotes also will be more accurate and can be better personalized to that customer’s preferences and needs. 

Streamlined Workflows

Using AI-powered CPQ tools helps to reduce the time from lead to conversion by using automated processes. You can also generate quotes faster, reduce time to approval, automate product configuration, and enhance accuracy and consistency.

Streamlining workflows also helps improve your sales process, customer experience, and save time.

Scalability

AI-powered CPQ software helps your ecommerce business to scale without compromising quality, cost, or time. These tools help by handling increasing amounts of users, data, and tasks.

For instance, it can help businesses manage a growing number of products, configurations, and pricing models without added complexity. 

AI in B2B Ecommerce Case Studies

Discover how B2B companies are leveraging the Zoovu AI-powered product discovery platform to improve their ecommerce operations.

GE HealthCare

For instance Zoovu helped GE HealthCare revolutionize the medical buying process by offering a visual product discovery solution for configuring their Vivid T8 Ultrasound machine.

This reduced the time both their internal sales team and buyers spent by 80% in searching, evaluating, and configuring the machine. It also ensured that the configured machine is compatible and compliant with their medical facility, thereby maintaining a safe working environment.

Dräger

Dräger, a pioneer in medical and safety technology, has transformed the customization of firefighter helmets by introducing Zoovu’s visual configurator to provide a self-service environment for buyers. This innovative tool allows firefighters to visualize all possible helmet configurations in ways that were previously unimaginable. while guaranteeing compliance and availability.

Additionally, by integrating the visual configurator, Dräger streamlines investment decisions, automates order entry and processing, thereby minimizing manual interventions and reducing buying errors.

3M

Using Zoovu’s AI-driven digital sales experience platform, 3M achieved a 2X increase in conversion and engaged 10+ channel partners by providing trustworthy self-service buying experiences. This was crucial as 3M buyers moved towards digital channels and needed to be 100% confident in purchasing products that were correct in usage and compliant with safety policies and regulations.

Zoovu helped 3M automate the compliance-based buying process, eliminating the need for 1:1 interaction with a sales rep and costly third-party specialists for product data tagging. Buyers can now understand different SKUs, find the right products based on usage and risk management, and 3M can generate conversational product content that reflects how buyers search for products.

The Future of AI in B2B Selling

As AI technology advances, it is reshaping both operational landscapes and customer expectations within B2B ecommerce. One significant area of impact is the rising demand for high-quality, automated self-service options. Modern online B2B buyers crave immediate access to information and the ability to complete tasks autonomously, without human intervention.

The effectiveness of AI-powered self-service tools hinges on the quality of underlying data. Clean, structured, and enriched data are crucial for optimizing these automated customer interactions.

If you’re seeking a product discovery platform that not only future-proofs your data but also crafts exceptional B2B ecommerce experiences to optimize sales and secure more deals, consider scheduling a free demo with Zoovu today.