AI In Sales: What Do The Experts Have To Say? (3/4)

How to effectively use AI in the sale process, to boost lead volume, close sales, conversation intelligence, effective coaching, and more?

Initium AI has recently hosted a discussion on the role that AI can play in sales, with sales and AI experts who shared their insights and experience:

Raluca Banea , Director of Strategic Accounts & Innovation at MedEquip Depot

Alex Gohl , Senior Director of Client Development at Syndigo

Rada Mihalcea , Professor & AI Lab Director at U. Michigan and Co-founder of Initium.AI

We are excited to share the third part of this conversation.

Highlighted here:

• AI to create a superior customer experience

Raluca: The next question is dear to my heart. In what ways can A I be used to create a superior customer experience? Of course, the customer is at the center of our world, right? In our business, we have two different applications: Searchspring and Klevu, both providing search capabilities. Our e-commerce platform is hosted by B-Commerce, which has its own native search. However, it's insufficient. Currently, we're using Searchspring for search, and we're very satisfied with the search results. However, due to the advancements in AI, I need to explore what more can be done with AI functionality in search.

The AI-based search systems can now understand queries in human language, which is really interesting. For example, if you're looking for black industrial gloves between $100 and $200, these systems can index the product catalog, extract products that fit these filters (color, black; category, industrial; product type, gloves), and even consider the price range. Moreover, they apply personalization based on your previous behavior on our site as well as on other sites. They also analyze the behavior of other users similar to you within their ecosystem. All of this happens in real-time, enabling the display of the most relevant content to you. I find this capability truly remarkable.

These AI-based systems can also provide product recommendations based on user behavior and preferences. Furthermore, you can customize these models to suit your specific needs. For example, you can assign more weight to certain attributes or values that are more important to you. In the backend, you can increase the weight of conversions over clicks, so products with a higher conversion rate from clicks are displayed first.

Another aspect is the predictive auto-complete, which we discussed earlier. We're all familiar with this feature from Google itself. As you type queries in Google, the search engine automatically suggests relevant search terms, and these suggestions improve over time.

Additionally, these AI-driven search technologies can find answers to common questions, not just about products. If you ask about our return policy on a website, the system recognizes your intent and provides the right content to answer your question. I find that extremely interesting.

Finally, real-time search is fascinating to me. As you search for certain keywords, the systems automatically generate synonyms and normalize measurements to better predict what you're looking for and display the most relevant content. Everything happening in AI-powered search is truly captivating, and I can't wait to see which solution we'll choose and how it will enhance the customer experience on our site. We have over 280,000 medical products, so it's crucial for customers to find exactly what they're looking for. The more we can leverage AI to get the customer closer to their desired products, the better. That's just one example I wanted to share, but I'd love to hear your thoughts, Alex, on how AI-based technologies can improve customer service.

Alex : It's interesting to evaluate our solution Syndigo, and consider how we can make it even better. We syndicate content to retailer websites and track conversion and impression data. We have a feature called enhanced content where suppliers can control additional information below the main pictures, such as manufacturer details. We conduct basic A/B testing for different types of content, but it's the same for everyone visiting the page. It would be intriguing to have more variations of content based on the visitor's profile. Personalization tends to have a greater impact on conversions, and I find that innovation exciting. From a tech stack perspective, we're focused on improving customer service by providing information to our reps assigned to existing customer accounts. We strive to optimize the number of accounts each rep handles, but it can be challenging to manage efficiently. We're adopting customer success solutions like ChurnZero that offer predictive capabilities and middleware to assess usage, contract scope, and potential risks. We want customers to get maximum value and aim to retain and grow their investment. These solutions help us serve customers better, as our solution is complex and involves multiple stakeholders. They provide efficiency and prescriptive insights for our reps to have meaningful conversations with customers.

Rada : Another complementary layer to consider is sentiment analysis, a natural language processing technology. It allows monitoring of customer experiences shared online, such as on social media. It helps react quickly to negative sentiments towards products or internally. I know your company, Ralph, has a great technological platform that can identify negative sentiments expressed in natural language, enabling prompt action. However, the volume of information can be overwhelming. It's important to also acknowledge positive comments and reinforce them for the company's benefit. Thematic is one company that analyzes customer feedback, and there are others that automatically analyze language to assist with customer experience.

Alex : When I used to work in an office for a tech company, we had a two-way wire where we would plug into the phone and sit next to each other to listen to calls and provide coaching to reps. It was an efficient way to onboard. Now, with conversation intelligence and AI, it takes all the data from customer meetings and brings major outliers to my attention. This helps me allocate time to review calls and potentially reach out to customers or provide coaching opportunities. It's not just about customer relationships, but also about how we can bring more value to conversations and be seen as a good partner. Conversation intelligence has had a big impact, especially when I compare it to the past when we had to physically sit next to someone to listen. Now I can listen to any call at any time and use analytics to evaluate things like active listening, two-way communication, and responsiveness. It's not just about meetings but also emails—how quickly they're replied to. It provides insights that weren't possible before, like tracking initiatives or new products and how they translate into opportunities. Looking back, the impact of conversation intelligence is tremendous.

Raluca : That's true. Another aspect optimized by AI is the duration of calls. AI systems have been able to reduce call duration by up to 70% by automating lower-level sales duties. This allows salespeople to focus on activities that generate income. The implications of these technologies are fascinating, and there are many great opportunities