Selling has gone through many evolutions in the past 50 or so years, but the mark of a good salesperson has always been the inherent ability to forge a relationship with a customer, not to sell a product or service. Traditionally, much of a salesperson’s time was spent on gathering information about the client company and, if possible, their contacts. Sometimes, the salesperson was lucky enough to have a researcher to help or a data vendor database to interrogate for this information. That was before the advent of digital marketing.
Today, the marketing practices of demand and lead generation, as well as lead scoring can qualify leads as never before. It is axiomatic that 80% of leads are not ready to commit to a purchase immediately; while in the past they would be dropped, they can now be nurtured until they are ready, when they can be handed to the sales department. So surely the sales force should be happy and motivated and achieve their targets? Well, no, because according to a report from Salesforce, they spend only 1/3 of their day actually selling.
Extract from “The State of Sales: Second Annual report” p18, by Salesforce Research, Nov 2016
Paving the Way for AI in Sales
According to the article published by InData Labs, there are three main roadblocks of AI implementation. These need to be removed before artificial intelligence (AI) can be added to the mix.
- Data Silos. Most organizations have spent time and money building a digital marketing environment. The best of breed have also ensured that the traditional marketing and digital marketing is fully integrated. What should happen is that sales (and the service team) should have access to the same data and the same views as marketing. This is not always the case. Sales quite often have a different, legacy CRM that does not have the richness of the marketing CRM, especially when it comes to lead qualification.
- Dysfunctional Processes. The company value chain needs to be improved. Respondents to the survey cited outdated processes and inefficient hand-offs between marketing and sales and sales and service.
- Unnecessary Administration. In the graph above, 25% of sales time is spent on administration. The process and data roadblocks amplify the administrative overhead with unnecessary tasks, such as producing sales reports, usually in Excel, from several sources. Cultural issues, such as lack of trust, often contribute to administrative overload.
Ensuring that each and every member of a sales team has access to the same customer information and insights as marketing and is empowered to make selling their first priority is a prerequisite for improving performance. In the report cited above, only 17% of respondents agreed that they had an outstanding single view of the customer throughout the business, which is essential for providing a great customer experience.
How Artificial Intelligence (AI) Can Lighten the Load
AI can boost productivity all along the value chain.
- Information can be extracted and patterned to give a comprehensive view of the company, including its relationship with competitors, its financial outlook and its risk profile.
- Information about contact(s) can be enhanced by interrogating social media sites, such as Linkedin and Twitter, and analyzing any previous interactions, such as buying patterns and lead time and email contents. Not only demographic data can be found this way, but also psychographic and personal interests outside of work. Unlike B2C marketing, there is generally more than one contact that a sales person has to build a relationship with, like a product evaluator or an RFP team, not only decision-makers.
- Lead scoring is a form of predictive analytics, where weights are assigned to every characteristic that can be gathered about a lead, both for the company and for the contact(s). The scores and the items that are scored are unique to the selling organization. The AI will build the lead profile by collecting data, and when the score has reached an agreed value, the lead is qualified and can be handed over to sales to start on the conversion process.
The Conversion Process
There is no substitute for face-to-face contact, especially in B2B marketing. While most office software can schedule calls and appointments, AI can be used to indicate a preferred day of the week and time of day at which the customer will be most receptive. There are even AI products that can act as a virtual assistant and a coach during the conversion process, using Natural Language Processing.
It is possible for a sales conversation to be vetted by this robotic assistant that can identify whether the customer is truly engaged and whether the salesperson is doing anything that could affect the success of the interaction, like interrupting the customer. The salesperson can then be prompted discreetly. Where this virtual assistant has been a silent listener to all sales conversations, it can analyze the content of the various interactions and identify what phrases and sequences are most likely to close the deal, like a digital NLP coach. This information can also be used both on the spot and for ongoing sales training.
Predictive analytics could also indicate whether a customer is ready to sign, so that the salesperson can prepare for closing. With an existing customer, historic lead times can be interrogated.
Reporting on sales would no longer be a tortuous exercise of extracting data about leads, prospects, conversion rates and dropped sales. The old way of reporting was usually subjective and based on guesstimates. With AI, an objective and unemotional view of each deal can be reported on, using the data gleaned from the sales conversations. What’s more, the administrative overhead on this would be zero.
Maintaining the Relationship
While all good salespeople are diligent in maintaining customer relationships, predictive analytics can keep a watching brief on the customer base and alert the salesperson when the customer is ready to make another purchase, or that some retention strategy is required, possibly due to a service issue.
This can be picked up via interactions (or lack thereof) such as emails or service desk conversations. The SalesForce report indicates in p.6 that today’s B2B customer wants a customer relationship manager, a trusted partner, who understands their needs and will not attempt to make unnecessary sales. They require personal attention and to feel that there is a valued relationship. However, they also want a 24/7 experience, via any channel they choose. Clearly, no human can be available constantly, but it could be possible in this case to revert to some AI, like using a chatbot, which will interpret and relay the message to their relationship manager.
The company that is quick to implement AI in the sales process for some, if not all of the activities mentioned above, will definitely have an advantage over their competitors in the short- to medium-term. However, they will have to keep raising the bar to stay ahead.