Predictive Lifecycle
In the past decade the B2B buyer has radically changed. Increased access to information has given buyers more power to control the sales process. At the same time the buying environment has become more complex as companies struggle under ever tighter budgetary and time constraints.
These macro-shifts have led to a segmentation of buyers and the sales people that sell to them. Forrester describes a 2×2 matrix where one axis is “solution complexity” and the other is “purchasing complexity”. In low-complexity environments sales people have less to do to advance a sale – and may be less necessary to generate sales relative to an e-commerce site, for example.
As complexity rises on either axis a sales person becomes more and more essential. They become critical to help shape the business case for the complex solution. And critical to guide the buying process as the buyer navigates internal political and decision making waters.
How Does this Impact Sales Teams?
The buyer journey for complex products is now a spider web of interactions between the buyer, her peers, and the seller’s go-to-market apparatus. The straight line from lead to opportunity to close isn’t a reality for complex sales.
A buyer may conduct early research on a business problem or set of solutions. She might take that information back to her colleagues, managers, and reports to see if there is a match between problem and solution. She may re-engage the sales person, or not. She might be influenced by marketing automation or sales outreaches. And this dance could continue for some time as a business case is built internally.
This complexity in the sale leads to a dramatic increase in ‘no decisions’ and companies that maintain the status quo. Confronting this issue requires sales leaders to address two major hurdles:
1. Who to Pitch?
According to Four Quadrant the average B2B purchase involves up to 20 people. When you have that level of complexity it is exceptionally difficult for a go-to-market team to identify who to work with and how to build internal momentum.
Further data from the CEB, the folks that brought us the Challenger Sale, shows that on average nearly 6 people had to OK a purchase before it could close. So, not only does the average B2B rep have to engage and get at least a neutral position from 20 different stakeholders but they also have to get the consensus thumbs-up from an approval group of about 6 people.
That is a tall order. Sales and marketing teams need to identify who they should target so that sales (and marketing) efforts are focused correctly. Organizations are opaque despite the increased visibility that comes from systems like LinkedIn. That’s because the power of individuals and their role in a buying decision can’t always be measured by their title.
2. What to Pitch?
In every sales situation, it’s as important to know ‘what to say’ as ‘who to say it to’. Prospects will respond to different messages in different ways depending on who they are and where they are in an organization or buying process. This challenge is exacerbated in a complex sale, with its longer sales cycle and larger set of stakeholders with competing priorities and agendas.
Lightweight datasheets and corporate overviews may work well sometimes, but a prospect in an advanced sales stage wants detailed information to construct their business case. That means providing different assets to prospects based on their situation.
A complex sale can involve messaging a complex product to address a complex solution. Or it could involve navigating a complex buying process where different buyers are trying to solve their own problems. In either case, most sales people will need guidance on how to navigate complex buying processes.
Further, ‘What to Pitch’ is more than just what to say. It also means what product to pitch in a given situation. Many B2B vendors have hundreds or many thousands of SKUs. Knowing which product to suggest to a new prospect, or knowing which product makes a great upsell to an existing customer sets great sales organizations apart.
What Works?
In the complex sales environment some reps consistently win. In fact, there generally is a set of 10% of your sales team that almost always hits quota. The remaining 90% may hit quota one quarter and miss it the next. That means there is something about what that top 10% is doing that we should try to repeat across the organization.
If you ask them, you’re likely to hear some variation on these two statements:
– “I know which prospects are likely to convert now. That’s where I focus.”
– “I know what to pitch to engage and advance my prospects to close.”
If you could capture that kind of insight you could focus your sales and marketing efforts, you could move beyond backward-looking approaches to complexity. That’s where a forward-looking approach comes in – predictive analytics.
Enter Predictive
Predictive analytics for sales use contextual and behavioral data about prospects and past results to predict future behavior. These predictions will never be 100% accurate, but they don’t need to be. They need to arm sales people with actionable data about likely outcomes so that better tactical and strategic decisions can be made. And they need to get more and more accurate at predicting likely outcomes over time.
These predictions help sales address the two primary challenges of a complex selling environment: ‘who to pitch?’ and ‘what to pitch?’. That is, providing decision support to better address the inherent complexity of the sales process.
Sales leaders have an array of predictive technologies at their disposal today that can help support decision making at the executive and individual contributor levels. These technologies process large volumes of data to identify likely paths for a prospect.
– Who to Pitch: Predictive technology primarily uses external signals like a prospect’s website browsing, social media activity, company firmographics, industry news, and even local weather conditions to predict which prospects will be receptive to your pitch and when.
– What to Pitch: Predictive technology uses a mix of internal and external signals like CRM/CSM/MA data, product usage, past buying behavior and responses to pitches to suggest what products and messaging will advance a prospect or customer.
Answering ‘Who to Pitch?’
Technologies like Lattice Engines, Neuralytics from InsideSales.com, 6Sense, Infer, and SalesPredict consume signals to identify which buyers a prospect should focus on. A sales person may have hundreds or even thousands of leads to filter through. Rather than gut-checks or brute force to prioritize leads and opportunities, these technologies score who to pitch next based on how a given prospect’s signals compare with other prospects conversion success.
These vendors’ software construct models that are unique to your organization, weighting different signals based on their predictive power. As your company processes more and more leads, the predictive model adapts to the new data. It constantly adjusts to the new situation to help sales teams focus on the people most likely to engage.
Answering ‘What to Pitch?’
Once a sales person gets a lead on the phone, or engages a prospect, or speaks to an existing customer they’re just part of the way there. The challenge of knowing what to pitch that prospect remains. So what will work?
There’s no one-size-fits-all for prospects. A sales person can’t say the same thing to every prospect and expect the same results. Predictive technology looks at contextual data about the sales situation, as well as behavioral data like which messages and content were compelling to similar prospects. Is there effective messaging for the given persona and/or industry? Did a particular sales play overcome a competitive threat? Did a piece of content help build a better business case?
At the same time, your buyer is not going to purchase just any SKU that the sales person pushes across the table. Certain products are more likely to be purchased based on the prospect’s past buying behavior when compared to others in similar situations. Predictive technology correlates these buying experiences and recommends to sales people what products they should pitch.
Decision Support for Sales People
The power of predictive is to reduce the complexity of the modern sales process. It helps sales people focus where they can add the most value – by speaking to people that are most likely to buy and offering them products and positioning that are most likely to solve their pain. Difficult decisions about who and what to pitch can be supported by technology based on likelihood of conversion. That gives sales leaders a radically powerful tool to focus their teams on transactions that are most likely to happen for the most amount of return.