Overview
During the National Retail Federation’s NFR 24 conference, Salesforce and Google released a slew of AI-powered tools aimed at reducing go‑to‑market (GTM) friction. These include for Salesforce some new Web page designer tools to optimize commerce conversions and reduce returns, as well as new product catalog, referral and loyalty management tools. Google has released a new set of chatbots for automated commerce, as well as some new self-service customer service tools and search optimization capabilities.
On the surface, much of these product announcements seem aimed at B2C GTM teams and general retailers. However, when we look at these innovations from a Converged Growth go‑to‑market lens, we see a number of potential applications for B2B use cases that drive enhanced post-sale growth endeavors.
GTM Innovation
For Salesforce the innovations announced at NRF 24 center on three topic areas. They include new site designer tools, promotion and loyalty tools, and a new prompt interface that is customer-facing and initially designed for online shoppers.
Here are more details on each:
- A new AI-powered Page Designer to optimize product display and information to drive conversions and reduce returns of merchandise. The tool uses generative AI-powered natural language prompts to design, build, and customize ecommerce sites and pages more quickly. Salesforce provides this example: A merchandiser can easily build a campaign landing page for a new line of running shoes by inputting a few prompts into Page Designer to quickly generate a new web page that mirrors the branding on its existing storefront.
- New Global Promotion Management tools join marketing data with AI insights to better approximate future pricing and craft more successful rewards programs, and new Referral Marketing tools, which can help build referral and loyalty programs and optimize usage and results.
- Segment Creation is designed to help retailers improve targeting and personalization using GenAI prompts, with data from inside the user’s Data Cloud instance. Users can quickly build new target segments that can be activated across marketing, commerce, service touch points for tailored journeys, offers, and recommendations.
- Copilot for Shoppers is an interesting new AI tool, as it is a new customer-facing chat tool that analyzes conversations (potentially across in store and online) to craft personalized recommendations and identify other buyer trends.
Google’s new announcements, on the other hand, focus on new chatbot tools, customer service (with a focus on self-service) and new search capabilities to optimize site conversions. All of these are purportedly AI-driven.
Let’s dig into each:
- The new chatbots leverage natural language processing to learn from the customer’s inputs – which can be used by B2B GTM teams with more complex product configurations and pricing models. Google claims these can be fully functional in a manner of weeks, versus multi-month or longer chatbot deployments.
- New search capabilities allow users to custom-tune large language models to personalize search results based on an individual’s actions. For B2B, this could mean identifying an account (not just an individual’s) past buying patterns and provide results based on their unique history and specific needs.
- New customer service tools allow not only for AI-powered virtual agents, but also allows human agents to cover multiple-engagement channels across pre-and-post sale engagement stages to improve the overall customer experience and take advantage of potential add-on revenue opportunities identified by AI.
GTM Implications
The obvious benefit for B2C/retail GTM use cases is clear. The AI-powered tools can help engage buyers, provide product and buying information and streamline post-sale return and support processes. The reduction in friction for commerce is clear for B2C users.
But these tools have value for B2B use cases as well when you consider the importance of looking at sources of revenue lift that come from all phases of the customer lifecycle. The web page optimization tools from Salesforce can be utilized by B2B GTM teams looking to build more transparent and commerce-oriented messages and flows for both new and return buyers.
Landscape Implications
For Salesforce, we see these new announcements as further evidence of their separating from other CRM-focused players when it comes to both AI and a broader narrative around supporting digital commerce for both B2C and B2B. While some players who focus more on the SMB and midmarket, such as Zoho, might have solid commerce tools growing, none of the other legacy enterprise CRM providers have really built out any modern commerce and full-journey support offerings to the extent of Salesforce. Oracle has some tools, but has been a bit behind in bringing an integrated, AI-powered cloud version of its offerings to market with any major noise.
For Google, it is always interesting to see how they will continue to separate themselves in the cloud arena. As Amazon always looms large on the competitive landscape, these tools counter the company’s existing contact center and chatbot tool sets across Amazon Connect, lens and other offerings.
For both providers, their continued focus on commerce may pit them more and more against the broader Adobe commerce-focused offerings in its portfolio. We expect to see a solid AI story around commerce and the Magento and related portfolio components from Adobe in its upcoming annual Summit in a few weeks. It will be interesting to see what Adobe has been developing in response to these announcements from Salesforce, Google and others.
The Takeaway
We like that key GTM technology providers are starting to offer highly consumable (at least in theory) AI-powered tools that go beyond the basic content creation and moderation use cases we have been seeing so far. Of course, chat bots have been in use for some time, but truly AI-powered, with a commerce focus rather than simple customer support use cases, is a new wrinkle.
Also, while these announcements were made at a retail-focused conference, do not underestimate the B2B significance of these new feature sets. With a strong Conversation Track Architecture in place, GTM teams can better automate revenue-growth across post-sale journey arcs – leading to more profitable lift and lifetime value per customer. As GTM teams build out their AI and overall GTM strategies, these tools can both fill gaps around full journey engagement and better optimize the overall post-sale experience and better streamline repeat business in B2B by leveraging known data around account’s past histories and populating web pages and offers with more pertinent and relevant products based on past purchases, the customer’s profile, etc. There is, in short, a great opportunity to leverage these tools to gain competitive advantage in B2B by creating more engaging, immersive and personalized experiences for anyone visiting your digital properties.
