Multi-Channel Selling in the New Era of Revenue Intelligence
“Customers want an always-on, personalized, omnichannel experience. The world’s best sellers are giving it to them,” states the McKinsey.com article, "The new B2B growth equation."
Revenue operations and intelligence solutions can mitigate the revenue and margin impacts caused by the broken supply chain, enable sales reps to sell excess and stockout inventory, and keep agreements priced to target and customers on track to hit volume commitments. But one more critical piece in the revenue operations and intelligence puzzle is seamlessly integrating revenue-driving actions into eCommerce and marketing automation systems.
As B2B companies seek to deliver a B2C, “Amazon-like” digital experience and leverage automated marketing solutions in a more tailored manner, making that vision a reality while ensuring a consistent customer experience between digital and sales team-led channels remains a challenge. Due to limited capabilities, most B2B companies simply serve up the same product recommendations to each customer that logs in to their online portal or can only highlight relevant products based on broad criteria.
Learn more: Top 4 Tips for B2B eCommerce
The good news is that revenue operations and intelligence solutions help create more consistent eCommerce and account-based marketing experiences by using data to automatically push highly relevant, personalized, account-specific actions into these digital channels.
Read More: What is Revenue Operations and Intelligence?
What Are Some Common eCommerce and Account-Based Marketing Sales Challenges?
Many companies have ecommerce systems that can display personalized product recommendations based on a set of logic and rules. Additionally, marketing automation tools are commonly used in a B2B setting to drive revenue through product promotions. However, it’s rare that these promotions are orchestrated in a manner that is coordinated and account-specific, or that the recommendations are generated using something other than manual analysis, such as AI. Further, measuring the revenue impact of these efforts is elusive. Let’s examine why achieving a more intelligent and coordinated approach to eCommerce and marketing remains so challenging.
Lack of Personalization
While there are eCommerce tools on the market that can recommend products to customers at the time of purchase in a company’s eCommerce portal, these tools typically offer static product recommendations or are based on overly broad rules. This means they simply serve up the same offerings to each customer, regardless of whether those promotions make sense for that specific customer. This approach fails to address the complexity inherent in large enterprises. For example, a B2B distributor may have tens of thousands of products and thousands of customers it serves. Ensuring that account-specific product recommendations are served up that grow wallet-share, recover lost purchase volume, win-back lost business, promote appropriate product substitutions and effectively sell stockout, excess or distressed inventory is critical. Additionally, without a means to intelligently deliver real-time complementary product recommendations at the time of order, based on the items in a customer’s basket, companies miss opportunities to grow their average order value. These tailored customer experiences are impossible with only static tools.
Lack of Consistency
Achieving the revenue and margin goals of the business hinges on how well you can capitalize on every customer touchpoint. For example, customers need to feel like they are dealing with a cohesive company that delivers bespoke pricing and product offers that matter to them. A consistent customer experience between online and sales-led channels is critical to achieving this experience. Without a centralized revenue operations and intelligence mechanism, sales-led channels, digital channels and marketing channels often recommend different items to customers at different times. A much more powerful approach ensures a cohesive experience such that the products one customer is served up online is consistent with the products their sales rep discusses with them as well as what they see in email marketing communications.
Limiting Manual Processes
The operational and analytical teams tasked with growing revenue in digital channels have been limited in the tool sets available to them. They are likely wrestling with enormous data sets and using spreadsheets to determine which items to offer customers. These items are likely to be matched based upon crude, too-large segments that fail to account for the granularity that exists in their customers’ purchase patterns. Ultimately, these manual tools and processes lack urgency and cannot keep pace with today’s real-time, always-on digital landscape. Manual tools also do not offer the necessary specificity to improve the customer experience in digital channels.
For example, let’s say a company’s product manager uploads a spreadsheet to serve up relevant products based on broad segments or promotions in the eCommerce portal. A significant amount of time was likely spent in pulling data from various systems, conducting analysis and determining the desired strategy. However, not only does this approach fail to address the granularity and complexity of most B2B enterprises, but it is also likely to quickly grow stale and irrelevant to customers. This completely misses the personalization mark. With revenue operations and intelligence software, the product manager can seamlessly serve up specific product recommendations for each account, quickly update those recommendations as conditions change, and ensure a unique eCommerce experience tailored to that customer based on data science and the latest data available on interactions with that customer.