Being in business-to-business (B2B) sales is a sprint, and a marathon rolled into one. It’s high pace and high reward; a complicated game of prospect keep-away between you and your competitors. In short, it’s intense. B2B sales staff have the benefit of specific products like customer relationship management systems and support from other areas of the organization, such as marketing and customer success. Yet, only for very large enterprises do effects of scale factor in the sales journey.
Sales teams function best when the salesperson has direct counterparts (i.e. a buddy system) with other subject experts. Some companies take this to the extreme and pair each salesperson with a marketing specialist and a sales engineer.
Only large organizations though can support this 1-to-1 matching strategy though because of the sheer amount of payroll it takes. This is not the only valid sales method. The best sales strategies are the ones that work well for your specific business; however, pairing sales with experts from across the organization is highly effective. For many businesses, though, having a functional buddy system is a challenge.
Imagine if every B2B salesperson, regardless of company size or revenue, could be paired with an assistant that is knowledgeable about marketing and also handles many aspects of ‘engineering’ the sale (that is identifying how customer needs and wants can be met by what is being sold). With artificial intelligence (AI) gaining traction as a business tool, it is no longer necessary to pair human-with-human. Now, the best buddy system may become one that matches a human sales expert with an intelligent computer program.
It’s Just Not Cutting It
Most organizations generate more leads than their team can engage, so they employ techniques like lead scoring to prioritize who gets the human follow-up. Marketing automation systems are good at assigning scoring points to demographic attributes, like title and email address, firmographic attributes, like company size and location, and behavior, like clicks, downloads, and page views. All is good and well when these values are known, but what happens when a high-value prospect registers with a personal email address and no title? A low lead score means no one follows up right away, and the opportunity to get into that two-way dialog is postponed or lost.
Even when the right leads get routed to the right people for engagement and conversion, it does not mean the person is easy to reach. After two or three attempts, it’s human nature to assume the person is not interested and move on to the next lead. But research shows that it often takes 7-12 touches to convert a lead, despite the fact that in most organizations, making so many attempts is not possible if each one is to be personalized. The rise of inside sales centers, power dialers, and local presence numbers have made reaching prospects by phone much more difficult. Busy prospects screen phone calls, even if they might ordinarily be interested, so it’s unlikely that initial outreach by phone will be successful in contacting, engaging, and converting that lead.
Research on the effectiveness of sales calls demonstrates the problem. In a study from Baylor University, out of 6,264 calls placed during two weeks:
- 17 percent were non-working numbers, 55 percent were not answered
- Only 28 percent of the calls were answered
- Of the 1,774 answered calls, 91 percent were not interested
- Reps had to make 209 calls to obtain one appointment or referral
- The overall success rate for the calling effort was 0.5 percent (30 appointments and referrals ÷ 6,264 calls placed)
Churning out enough phone calls to convert enough leads is beyond the endurance of even the strongest sales reps. But there is a silver lining: research shows that when a phone call is preceded by an email conversation, the prospect is much more likely to take that call and have the conversation that converts them into a meeting or sale.
Knowing that getting a prospect into a live phone conversation is a challenge, almost every business also uses email outreach. An email has the advantage of allowing prospects to determine when and where to engage, increasing the likelihood of a productive conversation.
But emails are also easily avoided, especially when they look like sales pitches or end up in the spam folder. In a well-cited analysis of email marketing campaigns, just 22 percent of emails were opened by prospects — a number that might work for broadcasting to a large business-to-consumer (B2C) audience but will not help create one-to-one B2B conversations.
AI is the Buddy You’ve Been Asking For
AI is changing how smart salespeople identify, capture, and delight new and existing customers. According to McKinsey, companies that use AI in the sales process can increase revenue generation by as much as 63 percent.
Salespeople should adopt AI as a part of their sales process because it increases the lead volume of the products, quality, and the close rate. According to the Harvard Business Review of B2B sales, AI can increase sales leads by 50 percent and reduce cost and time up to 60 percent. Another value that AI provides in the sales process is digesting large volumes of data to suggest actions to sales teams.
The best AI assistants work with the systems you already use. By directly integrating with your store of customer data, you will visualize and act on real-time intelligence without having to navigate to a separate program on a different screen. AI allows salespeople to spend more time on productive outreach, and less time on low-quality prospects which would never have converted.
There are some significant limitations through to what AI sales assistants can help with. To provide insights, these tools need to see other similar data points in the system of record. For example, if you are trying to predict cross-selling opportunities, the system will need to see instances for those that have purchased either product (but not the other) and those that have purchased both. If either one of these data points is not available to the AI, it cannot provide an accurate recommendation.
Another key limitation for AI sales assistants is information centralization. To function effectively, these systems need to have access to the complete customer record (e.g. documents, past interactions, current purchases, etc.) at the same time. If part of the customer record is outside the main data store, or not stored in a system at all, the AI may likely miss signals in the data that would help it accurately predict buying behavior.
AI and You
AI is a great equalizer. It provides ways for companies that have historically been unable to support a direct sales-marketing staff pairing with the next best thing: real-time predictive insights. When sales staff use these insights effectively, it turns them into superheroes. More productive outreach, higher conversions, and the ability to contact the customer while the problem they need solving is top of mind for them.
Many organizational challenges must be overcome for AI sales assistants to become commonplace. Data integrity and centralization are key to this effort. But as more and more companies adopt a single source of truth for customer information like a CRM, or an industry-specific system like an agency management system, these problems become less of an obstacle. In the highly competitive sales landscape, AI provides a way to distinguish yourself from the competition and reach your customers before anyone else.