Artificial Intelligence Drives Advances in Improving User Experience

Building a B2B platform that optimizes the user experience depends on lots of data and business intelligence, or BI. UI/UX (user interface-user experience) development depends on this information, but how does a company obtain, store and use BI? The simple answer is third-party BI integrations and an integrated platform that gathers information from every website activity and disseminates the data to every operating system and the business applications. The information helps staff members make decisions about things like promoting certain products, offering sales incentives and adding more stock to inventory.

Learning about customer behavior, feelings and other characteristics helps marketers and staff make important decisions about how to tailor the platform experience to each customer and B2B decision-maker. Full platform integration facilitates the automated collection of data and cross-channel information-sharing in real-time. Machine learning modules can make even better connections by learning what a customer has done in the past, what similar people are buying online and trends that are prevalent in social media. There are some eCommerce platforms, like Clarity eCommerce that have an available machine learning module. That module can watch a user’s behavior and automatically make decisions like serving up a 10% of hand tools coupon, when it sees that 75% of the time, the user browses hand tools versus power tools, for example.

About 44 percent of salespeople give up after just one follow-up call. [1] Computers don't get frustrated or give up after failing to convince customers once or twice. Systems can be programmed not to bombard customers with annoying offers but to recommend relevant products or incentives at appropriate times. Learning modules become more sophisticated as they gather behavioral data--for example, learning what time interval produces the best results when sending follow-up communications and marketing incentives.

Artificial intelligence, or AI, isn't the exclusive domain of speculative science fiction tales where robots take over the world. The technology is here and being used by savvy companies as marketing, manufacturing and operating tools in all areas of business. Examples include voice search, proprietary apps, data systems and user experience development. AI can be used to bring together smart technologies, learn from experience and make suggestions to staff members and customers based on unadulterated observations. Some of the ways that machine learning is transforming eCommerce include:


  • Chatbots can be used to offer customers a better search experience by helping them find appropriate product categories, compatible parts and workable alternatives to components that are no longer being manufactured. Chatbot technology is used by the most successful online marketers such as Amazon, eBay Rakuten, iTunes, Google Play and others. However, any company can begin improving user experience by offering the technology--the costs are not prohibitive for SMEs.

Data Management

  • Integrating data management systems with AI generates astonishing insights into customer preferences, BI trends and lead management. Companies can identify sales opportunities faster, streamline administration, automate alerts and marketing messages and create more personalized journeys for each site user.

Pattern Recognition and Tracking

  • Within data, there are intelligence insights about customer loyalty, marketing opportunities and ways to increase customer satisfaction and retention. AI insights can identify the best sources of actionable information such as product reviews, customer comments, user forums and social platforms. Customer feedback across the web can be analyzed to synthesize typical buying patterns across many channels.

Speaking the Right Language

  • It’s important to create content in each user’s native language to get the best sales results. However, people also speak a different way within a given language. For example, the target audience be people who hold graduate or undergraduate degrees. Knowledge of demographics can help companies to create content that appeals to an educated group or a group of blue collar workers who handle routine maintenance jobs and want simpler product descriptions.

Using Data-mining to Increase Sales

Improving the customer experience can be summed up succinctly: Make things easier for each customer based on his or her known preferences and common buyer attitudes. Data-mining can provide deeper insights into customers by monitoring social media platform activity. It’s useful to know that buyers of product X also tend to buy products Y and Z. It makes sense to display products X, Y and Z together. Amazon manages this sales strategy brilliantly by displaying groups of products that buyers also bought after buying a particular item. [2]

Data-mining helps companies design the sales journey to follow the path of least resistance. Many companies work to reduce the number of clicks that users make, but in today's fast-paced mobile-marketing world, even a few clicks can be too many. Data-mining can reveal insights into how groups of customer behave--such as educated customers always researching the supply chain or new customers concentrating on price and payment security. Companies can reinforce the appeal of their products by addressing each customer’s most likely concerns.

Hiring the Right User Experience Developers

The best user experience developers have experience and skill in B2B marketing, platform development and integrating business applications. You might need to integrate third-party BI sources, proprietary apps and CRM and ERP software to get the best results. It’s important to ensure that your designer/developer understands the demands of UI/UX development. The ideal vendor will work with you to integrate an AI module into your system, work collaboratively with product managers, touch base with marketers for their input and design a seamless customer journey that follows the path of least resistance to deliver optimal customer experiences.


[1] 50 Unbelievable Lead Generation Statistics that Will Make You Hustle

[2] How Data Mining Improves Customer Experience: 30 Expert Tips

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