"Distributor’s Playbook to Artificial Intelligence” Series Recap
Part 1 “Understanding AI and How it Works,” the first of three whitepapers in Proton’s series with NAW, looked at how technology-first companies like Amazon and the change in sales environment due to COVID-19 have heightened expectations around the customer experience, even for B2B buyers. These new customer expectations can be met with AI.
Distributors can expect AI solutions to scale exponentially. That means processes influenced by AI will continue to grow in value rather than plateau like traditional operating models inevitably do.
Behind that growth is data. AI solutions need very large data sets in order to make accurate predictions. Distributors can use the data they already have, generated by transaction history along with data from CRM, ERP, eCommerce, product catalogs, and more. The data may be noisy, but deep learning models can reach high levels of accuracy despite the noise.
Part 2 “AI-Powered Personalization: From B2C Sales to B2B Distributors,” second in the series, takes a deep dive into how B2C companies have leveraged AI technology to win big, including case studies on Home Depot, Netflix, and Amazon. AI-driven personalization, based on individual actions and behaviors from each user, is the common thread across all three.
AI-powered personalization can be utilized by distributors with the data they already have and continue to obtain. Through personalization, distributors can deliver content users want to see, tailor consistent omnichannel experiences, and offer relevant upsell and cross-sell opportunities. This personalization works across digital contact points as well as AI-guided human interactions with customers. Humans still play an important role in advising customers and helping them navigate product discovery and complex orders.
By starting with personalization, plus a plan for integrating AI throughout the organization, distributors can create a data network effect. This is where more users leads to more data, more data leads to better analytics, better analytics leads to a better product, then better products lead to more users. This enables a cycle of continuous improvement that improves the customer experience and increases sales.
Applying AI to Sales For distributors who want to use AI in their business, starting with sales and marketing will deliver the fastest ROI. AI’s place in sales and marketing is to enhance the customer experience through personalization, ultimately realizing the goal of increasing revenue. Keep reading for use cases that illustrate how distributors can employ AI to improve their sales channels and what strategies will help overcome obstacles to successful AI deployment.
AI Use Cases for Distributors
Gartner predicts that by 2025, 75% of B2B sales organizations will augment traditional sales playbooks with AI-guided selling solutions, and for good reason. B2B buyers are, in their personal lives, B2C shoppers. Moreover, close to half of B2B buyers are millennials who expect a personalized, Amazon-like experience and streamlined digital channels when making buying decisions for work.
The degree to which distributors can meet that expectation will increasingly determine business success. That means implementing AI across the sales use cases that we explore in this paper.
How Do I Increase Revenue with my Existing Customers? Everyone accepts that the cost of acquiring a new customer far exceeds the cost of keeping a current customer happy. But what about the lost opportunity cost incurred when you fail to optimize that existing customer relationship to drive greater wallet share? That hidden cost can be significant.
Three major factors keeping distributors from maximizing revenue earned from each customer are: reps waiting for customers to reach out when they need to order products, not upselling more of the products being sold, and not pitching additional products that may meet the customer’s needs. AI can help reps begin proactively selling, increasing revenue per rep and boosting your company’s wallet share with customers.
By mining transaction history for each customer, AI can identify patterns and trends to predict when a customer will be ready to re-order. The AI system can send a “next best action” prompt to the relevant rep, who can reach out proactively to the customer and protect wallet share by capturing that re-order.
During that re-order interaction or any sales conversation with the customer, reps need to be pursuing new revenue opportunities by upselling and cross-selling the products that customers are likely to purchase. This requires deep knowledge of your product catalog and your customers’ businesses, typically limited to reps with years of experience.
Alternatively, AI-generated product suggestions can guide reps to making relevant suggestions, including:
• Similar products that offer different or additional features and benefits
• Items that logically go with the original item ordered, such as safety goggles with work gloves
• Items that fill the same need if inventory is not available in the customer’s designated delivery window
• “Switch and save” opportunities to replace the ordered item with a similar product that performs the same function (not an immediate wallet share increasing tactic, but one that builds customer loyalty)
How Do I Increase Revenue that Flows Through my Digital Branch? With the growth of digital-savvy millennials among B2B buyers, as well as the influence of COVID-19 and digital-first businesses like Amazon, we are seeing buyer behavior becoming more oriented toward digital and self-service than ever.
In response, distributors must meet customers where they want to buy – on the internet – whether that is via a marketplace or your own direct-to-customer website. The reasons are twofold: protect your territory and increase your profit margins. If your
competitors are selling the way customers want to buy and you are not, you will see your customers defect in favor of the seller with the best digital experience. Make no mistake, there are B2B digital predators out there, including Amazon Business, that are pursuing your customers by empowering them with self-service where it makes sense in the buyer journey, offering new sources of value, and increasing operational agility.
At the same time, digital channels offer better margins because a website can handle exponentially increasing sales volumes without the overhead of human sellers. Promoting digital channel adoption among your existing customers will bring down your cost to serve and increase your profitability. Consider this important equation:
You can influence the number of sessions through drive-to-web marketing, including social media and special promotions. For example, you can offer lower prices for digital purchases and, thanks to better margins, still maintain profitability. Your reps can also help with drive-to-web by following up on product pitches and other conversations with emails that include relevant links to your website.
Conversion rate and average order value (AOV), however, can still suffer if there are flaws in your digital execution. For example, irrelevant, incomplete, or not entirely relevant search results can hurt your eCommerce experience and hinder digital adoption by making it difficult for your customers to find the products they want. Additionally, not putting relevant product recommendations in front of customers that are actively buying on your website is a failed opportunity to increase their order value.
Using rep-like “thinking” (machine learning models) for suggesting products and increasing AOV, AI-powered product suggestions put items customers are likely to buy in front of them while they are on your website. On a product page, AI can suggest an upsell, such as showing the savings from buying 12,000 screwdrivers instead of the 10,000 your customer usually orders. “Frequently bought together” suggestions show related products, such as Alan wrench sets with screwdriver sets. At checkout, you have another opportunity to suggest related items using a “complete the cart/kit” prompt with related products.
How Do I Get New Sales Reps Ramped Up Quickly? To be successful, reps need to know who to call and when, as well as what to talk about when they have a customer or prospect on the phone. They also need to spend time honing their selling skills rather than doing administrative work like creating call lists. AI can help distributors’ new sales reps get to where they need to be quicker by addressing these requirements.
Calling on the right account at the right time is critical to making sales. AI can analyze account attributes, purchase history, similarities between accounts, and more to determine when that time is – and AI does this analysis in much greater depth and speed than a rep can do manually. Plus, manual research like this is a time-consuming administrative task that keeps a seller from selling.
An AI system tuned for your business can detect those patterns in buying behavior, identify accounts that are likely to make an order on or around a particular time, and provide reps with a list of accounts to call today, ranked in order of priority. AI can also determine if a customer is likely to churn based on a slowdown in buying behavior and prioritize them as high-risk in the call list. This significantly reduces the knowledge new reps need to accumulate on their accounts before they can begin to effectively prioritize them. The result is more time spent making calls and greater rep effectiveness due to focusing their efforts on high-potential accounts.
The next challenge distributors face in bringing new reps up to speed is getting them familiar with a product catalog that has thousands upon thousands of SKUs. Providing customers and prospects with the information they need while they’re on the phone enhances the customer experience and increases the chances of making a sale. Even seasoned reps with 15-20 years of experience can’t possibly know details on every product with a catalog of 100,000+ SKUs. For new reps, it’s a massive obstacle to success.
Instead of training the reps directly, distributors can use AI to search product catalogs. AI can read and interpret text from product descriptions as well as PDFs of product literature, enabling reps to search by topics, keywords, or features. Quick and precise searching allows reps to find the right products, pull up detailed information, and answer questions or provide information in real-time while on the phone with customers.
With this capability, minimal training is required to make even new reps appear as product experts and bring value to the customer. That frees up resources to focus training on how to craft solutions for complex sales situations, where the customer value and return on investment are higher.
Securing Broad Adoption of AI in your Sales Organization
How you go about introducing AI technology to your sales organization is critical to the success of your program. According to McKinsey, only 30% of change programs succeed, and lack of a strong foundation for change is a leading culprit. While the heart of an AI program for distribution sales and eCommerce is to increase seller effectiveness and revenue generation, many people fear AI. They may think it will make their jobs obsolete, particularly sales reps who may feel their deep knowledge from many years of experience is being codified in AI algorithms. Moreover, unless positioned correctly, efforts to move customers away from traditional sales to AI-supported online self-service can further fuel that concern. Employees may also be concerned about acquiring new skills needed to work with AI. Most importantly, they must trust the results and recommendations of an AI system designed to help them make better selling decisions.
To ensure the adoption of your new AI-based sales tools and resources, distributors must first make sure that the tools will benefit sellers in the way you envision them. Then incorporate change management, including employee communication and user training, as essential components of your AI program, not afterthoughts. Here are three components of change management that are essential to a successful AI program rollout.
Creating Buy-in. Perhaps the single most important step is to make sure you have strong leadership support for the technology rollout from the outset of program development. Focus communications on how the tool benefits sales reps by removing time-consuming administration tasks and focusing seller efforts on high-value opportunities. As the program rolls out, over-communicate success stories.
Mitigating Resistance and Fear. Make sure sales reps understand how the new technology helps them sell more – and emphasize that it is designed not to replace their efforts, but to enhance them. Also communicate clearly how moving low-value or commodity purchases to self-service gives them more time to pursue higher value and higher revenue opportunities. Reassure them that the technology may make recommendations, but the human is the final authority. Be transparent about how machine learning models work and the data they use. Moreover, have sales managers, not HR, train reps on the key features and functionality.
Promoting Adoption. As sellers see others and themselves realizing success, adoption is likely to follow. But at the outset, it is important to set clear usage expectations and track usage as well as results. To prepare them for success, train reps on the “art” of selling alongside training in using the technology. If you want reps to use their newly available time on higher-value opportunities, equip them to solution and manage complex deals.
Distributors have significant opportunities to capture greater wallet share, get new sellers up to speed quickly, and increase eCommerce revenues by using AI technology. Using sales as your AI proving ground can help you get up and running quickly and realize ROI faster. Address these use cases by applying core AI capabilities to your sales arsenal:
• Predict when customers are ready to buy. Add AI to your sales playbook by using it to analyze things like customer purchase histories, lookalike customers, and seasonal factors to predict which customers are likely to order or re-order, and when. AI-driven “next best action” tools can use those predictions to create daily call lists for sales reps, prioritizing the accounts to focus on. This also relieves reps of time-consuming, manual tasks like researching accounts and figuring out which ones to call next so they can spend more time on high-value customer actions.
• Deliver relevant upsell and cross-sell suggestions. Whether it be on your website or on a call with your reps, delivering relevant product suggestions is a surefire way to increase the revenue you get from each customer. AI can learn your product catalog to find similar items, products that tend to go with one another, and more in order to amplify your sales channels and increase the revenue from every customer interaction.
• Make your reps product experts. With the numbers of SKUs distributors have, it’s impossible for any one rep to have adequate knowledge on every single one. Without knowing each product and the problem they solve in-depth, it’s difficult for reps to consult customers and add value while they have them on the phone. With AI, you can enable reps with the ability to search your product catalog in a variety of ways, and ultimately help them enhance the customer experience.
• Invest in AI-powered search. The primary impact of using AI to enhance search relevance will be increased eCommerce revenue — and happier customers. Distributors can also use that technology to help counter sales reps locate products and substitutes and make it easy for telesales and field sales to find the right products for their customers.
The clock is ticking on the advantages you can realize with AI. Early adoption can be the difference between 122% and 10% gains. To win, distributors must establish a firm foothold in the B2B eCommerce space or find their customers defecting to digital predators like Amazon Business and other marketplaces. Distributors must also equip their sales and customer service reps with the tools they need to be effective and add value to the customer relationship.
Acquiring AI capabilities through a vendor will be much faster and cheaper than building AI expertise and solutions in-house. But if you’re going to pay for a vendor, it’s important to choose the right one. While there are many AI vendors out there, it’s important to find one purpose-built to handle distributors’ “noisy” data, high SKU counts, and multichannel buying processes.
About Proton.ai Proton.ai was founded in 2018 by Benj Cohen, fourth-generation distributor and Harvard alumnus. Proton is an AI-powered sales enablement platform, purpose built to increase revenue for distributors by helping sales reps and customers navigate the complexities of managing lots of products through multiple channels. Proton helps distributors grow revenue by 5%-10%+ and gain market share.
About NAW The National Association of Wholesaler-Distributors (NAW) is composed of direct member companies and a federation of international, national, regional, state and local associations and their member companies, which collectively total more than 30,000 employers, with locations in all 50 states and the District of Columbia. NAW-affiliated companies are a constituency at the core of our economy—the link in the marketing chain between manufacturers and retailers, and commercial, institutional and governmental end users. Industry firms vary widely in size, employ more than 5.9 million American workers and account for $5.3 trillion in annual U.S. economic activity.