By Jennifer Stanley
McKinsey & Co.
B2B sales leaders who use digital effectively enjoy five times the growth rate of their peers who don’t. But a recent McKinsey & Company survey of B2B customers highlights a more nuanced reality. What customers want are great digital interactions and the human touch, depending on what they’re trying to do.
Companies that respond to customer preferences and add the human touch to digital sales consistently outperform their peers. They capture five times more revenue, eight times more operating profit and, for public companies, twice the return to shareholders. This data holds true over a four- to five-year period.
Many sales organizations, however, have trouble putting this human-digital program into practice. The truth is that there are no tried-and-true methods, though technology lies at the heart of customer interaction models to power or inform either the digital or human interaction. Companies need to create the human-digital blend that is most appropriate for their business and their customers. This should not be a random process of trial-and-error testing. What is needed is a systematic way to evaluate the optimal human-digital balance.
This human-digital balance is thrown into particular relief when it comes to artificial intelligence (AI), which is having an impact not only on the broader selling profession but also on strategic account management (SAM). Take, for example, the case of “Andy,” a bot introduced recently by a company to help identify, contact and set up appointments for SAMs at their customers. These appointments were in customer business units that had been either unserved or underserved and that displayed decentralized, regionalized buying behaviors.
Andy’s key capability is her ability to rapidly learn what kinds of outreach and communications are working and to instantaneously adapt her methods to suit. After just a few months, new leads were up 50 percent compared to the year before, while new costs for obtaining those leads were down.
Bots are already managing relatively mundane tasks like this at many companies, but could a bot like Andy manage an end-to-end sale for something like a transactional good to a small- or medium-sized business? Researchers at McKinsey Global Institute (MGI) have studied more than 2,000 discrete human activities across 800 professions, in 50 different countries, to assess the degree of “automatability” of activities in those professions. In some cases it was 100 percent; in others, it was zero. For management professionals, like SAMs, it was around 30 percent.
Comparing skills that are most crucial for the SAM role — things like managing teams, co-creating value with a customer, managing stakeholder interactions and others — with other types of activities that we don’t traditionally think of as part of the SAM role, the three most essential SAM tasks are only marginally automatable.
Figure 1. The degree of automatability of tasks by bot (left side) and by humans (right side).
But do customers want to interact with machines? The answer depends on context, as figure 2 shows. Figure 2 shows the research on how customers buy. The answer: It depends on the context.
When working with a new supplier or vetting a new offer from an existing supplier, 75 percent of customers say they want to deal with an actual human being. As customers move into the evaluation and active-consideration stages, digital tools that provide information, such as comparison tools or online configurators, come into their own, especially when combined with a highly skilled salesforce. When it’s time to renew or update standard terms and conditions, the equation flips, with 85 percent saying they prefer a fully digitized interaction.
In essence, buyers are saying that when co-creating something new and different with a strategic supplier, they’re all for engaging with the SAM. Yet most B2B companies still reward reps more for spending time keeping customers loyal and repurchasing than for uncovering new customer needs or driving demand, which is exactly where customers say they want face-to-face expertise.
So there remains a time and a place for intimate, significant human interaction, and there is a time and a place for bot interaction. The trick is to understand which is which and to adapt the strategic account management approach accordingly.
In particular, there are five areas where humans are needed and can do a better job than AI-empowered machines:
#1: Managing exceptions to standard protocol. Advanced analytics and machines get it wrong a lot of the time, and sometimes you need a human being to actually make the call. A materials company during the height of the economic downturn faced a situation where one of its strategic accounts was experiencing a credit crunch. By any kind of financial or data-driven standard, this supplier should not have extended additional credit to this customer. Now, what a machine couldn’t know is that this was a family-owned business and that the father was getting ready to retire. One son had been tapped to take over the company, while another brother worked at a key competitor that also happened to be one of this supplier’s strategic accounts.
So while the decision not to extend credit may have been “obvious” based on the data, the head of strategic accounts, who was familiar with the situation, worked with the father to find a solution. In the end, the father was happy, which made both sons happy — and which kept both strategic accounts in play.
#2: Using judgment in situations of ambiguity. When data is new and unlike anything that a machine has seen, the machine won’t know what to do with it. That’s where managers come in.
A company may be in an industry experiencing substantial mergers and acquisitions or business closures. In a merger situation, it is highly likely that the customer having the more advantageous terms with a supplier will ask for those same terms for the other account. It takes human judgment to plow through those terms and conditions and to make tradeoffs based on the role the strategic account(s) plays in an overall portfolio.
#3: Shaping strategy. Humans still must shape the overall commercial strategy in light of their growth goals — even if machines take over part of the work, like analyzing buyer trends, determining new sources of growth or predicting whether accounts are at risk of full or partial churn.
#4: Nurturing a complex ecosystem of relationships. Because today’s customer-supplier ecosystem is so complex, with interconnected webs of relationships including those forged digitally, it requires even more thought to select the most appropriate people to invite into the ecosystem and then to manage the content shared with them. SAMs need to determine not only who is in the network but also on whom to focus at different times and in different situations with the customer. This requires SAMs to know who are the most influential decision makers within an account and to build this knowledge into their account plans. While there are tools today that can illustrate the breadth and depth of relationships based on social media presence and suggest who are the influencers, such machine-based data still cannot replace you knowing your customer deeply –- who is on the way up, who is on the way out and who you will need in your corner. When we rely too much on the data to tell us how our customers are likely to behave and not enough on our own intuition and personal knowledge, that’s when SAMs can run into trouble.
#5: Focusing the power of advanced analytics. SAMs should embrace advanced analytics for their ability to help us to have more, and more productive, value-creating conversations with strategic customers. This is the area where AI can make our jobs not only a lot easier but also a lot more fun.
This means taking the data for what it is but then testing and retesting it. If the data suggests ways to generate additional volume, grow revenue, cut costs — whatever the outcome is that you’re looking for with your strategic account — you can pilot, you can test and you can learn. But you still need to use good business judgment. For example, experimenting with next-product/service-to-buy algorithms can support cross-sell activities, but if it’s not a good time to have the conversation with the customer, those activities need to wait.
To stay ahead, there are two areas where SAMs need to raise the bar in terms of using advanced analytics to help deliver on customers’ needs:
#1: Know your products, services and data offers much more intimately than you do today. Customers today have access to a wealth of information about your offerings via digital platforms and their own personal networks; if they are going to have an actual conversation with a SAM, they expect a deeper level of insight and expertise than what they can find online.
#2: Become an expert advisor. Data is best at suggesting different options, but where humans can provide the most value is in making decisions using that data. SAMs need to get good at making sense of data to make better decisions. For example, there is a global producer of wind turbines that uses AI and big data to guide decisions on where customers should locate their next round of turbines. But even with this data, succeeding with large customers still requires a SAM to have a nuanced, highly informed and consultative conversation with stakeholders whose job it is to decide where to build and place the turbines. While data like barometric pressure, predicted weather forecasts, topography, population demographics and more are critical inputs to those decisions, humans still need to choose whether or not to follow the data in light of other investment considerations.
In the end, the biggest benefit of AI to the SAM profession may be in its ability to make the job more fun. SAMs spend only about 10 percent of their time on creative pursuits, such as brainstorming new offers. With all the time SAMs currently spend making appointments, following up on invoices and putting out fires at the customer, that is time that could instead be spent coaching teams, boosting social and emotional intelligence, and on other high-value activities. This is where the bots can step in and help. SAMs should embrace the bots for what they can do to free up time that can be spent doing more interesting and creative things – like becoming more human with their customers.
Jennifer Stanley will deliver a keynote address at SAMA’s Pan-European Conference 14-15 March 2019 in Amsterdam.