From PROS, John Bruno, VP of Strategy and Justin Silver, Senior Manager Data Science, discuss how AI will play a role in the future of B2B customer experience and wider business processes.

Digital customer experience (CX) has never been more important than it is today, with buyers reliant on online platforms to access products and services. Rather than just a wave of online shopping amongst consumers, B2B online shopping increased by almost 25% in 2020, with a total of 46% of purchases made this way. This can’t merely be dismissed as a necessary evil due to the pandemic: over 75% of B2B purchasers say they prefer purchasing online and having remote interactions with sales reps.

Business buyers expect the same frictionless and streamlined CX in their B2B interactions that they receive from consumer sales. Offering an omnichannel experience is crucial to satisfying customers, however the more channels an organisation supports, the more opportunity there is for data to become unintentionally siloed across different platforms. For example, the sales team may use one system with certain prices for products, whereas the e-commerce team may use another system which has different prices for those products. An AI-empowered platform can identify and leverage data from multiple locations in a business, enabling the management and optimisation of pricing across various sales channels. By implementing this, CTOs can empower their sales teams to adapt to every customer and transaction in a dynamic and flexible way. For example, AI and data enables businesses to adapt more nimbly to market changes such as inflation, facilitating price adjustments across various platforms and in between these waves of volatility without teams being required to go through cumbersome manual processes. This ultimately protects their buyers from market volatilities, especially those that have an impact on the price of goods.

CTOs must also remember that in the digital selling world, the majority of customers nowadays are over halfway through the buying process before they ever meet with a sales rep. Rather than the first engagement being with an uninformed prospect, your customers are already steps ahead of you in what they know. Therefore, CTOs need to ensure sales teams have accurate insight into where a customer is on the buying journey. Having access to these AI-leveraged data points gives context to reps and allows them to understand the problems they can solve and add value to the customer’s journey. This ultimately empowers the buyer to be more autonomous in their journey. With 54% of millennial B2B buyers reporting that they prefer a rep-free experience, ensuring that sales rep input is always valuable and minimal will be the way to optimise CX going forwards.

AI can add huge value to sales teams and, as a result, customers, however it must be implemented correctly and integrated fully into operations in order to create meaningful results, according to Justin Silver.

The future of AI in business

Justin Silver, Senior Manager Data Science, PROS

As digitisation in our world accelerates dramatically, organisations are moving faster than ever before to rework business processes. A growing priority for business leaders is determining how to best utilise AI to increase the efficiency of those processes and drive maximum value for their organisations. However, it’s important to note that implementing AI is not just a matter of tacking on another solution to existing business processes. Instead, business leaders need to work on identifying the most strategic ways to implement AI and make sure buy-in is felt across all members of the organisation.

We anticipate an acceleration in the digitisation of business operations. Retailers have been using online sales channels for many years, and we are already seeing B2B companies follow suit. As the effects of the pandemic continue to transform how people buy and sell, we will see a shift to digital commerce in industries where human interaction and negotiation still play a significant role in sales transactions.

More organisations will further implement automated pipelines based on AI platforms. Data scientists’ day-to-day tasks, such as data preparation, feature engineering, and modelling, are being augmented by tools that help automate these steps. More systematic implementations of business AI solutions are expected to make ad hoc analyses more efficient and repeatable.

Businesses that implement AI systems that learn from continuous feedback generated by real user and customer interactions will be better able to provide the buying, selling, and operational experiences that their customers and employees are increasingly expecting. As a result, these companies will be in a better position to see a return on investment from their AI solutions.