People Dig the Long Ball…
I was at a golf practice range the other day. I took a nice, easy swing, heard that ultra-satisfying “click”, and watched the ball travel straight downrange and land exactly where I intended it to. And for a moment, one brief, fleeting moment, I actually believed I was getting better at this game. Then I took four more swings and sprayed the balls from one side of the range to the other. Just like that, my dreams of being on tour with the PGA were crushed, yet again.
I leaned on my 7-iron for a moment and looked around. There were probably 30 or so other people, most of them with frustrated looks on their faces and swinging away with all the grace of Paul Bunyan. I noticed something interesting; aside from two or three other people, all were swinging a driver of some sort, aiming for that 300-yard target far downrange.
Now, if you’re really, really good (top 5% of golfers) you’ll hit a ball an average of 80 times over the course of 18 holes. For most of the rest of us, we’re hitting a ball up to 100 times. You’ve got 14 clubs to choose from, each designed to send the ball downrange to different distances. The most important piece of advice I got where golf (and life) is concerned is this: You’re going to use your drivers, the clubs used to send the ball the furthest off a golf tee, only about 16% of the time. The other 84% of the time you’re using some other club, so spend your time wisely when it comes to practicing.
So why all the fascination with the drivers? Why was most everyone gauging how good a golfer they were based upon how well they swung a club that’s used 16% of the entire game, at the beginning of a few holes? Why is so much technology poured into drivers by the club manufacturers? Why is there so much marketing around drivers? I’ve got a couple of ideas why. First, people dig the long ball. It’s impressive to see somebody hit a ball long and straight, over and over again. Fewer people are paying attention to you in the middle of your game, but your whole foursome is watching you step up to that tee and swing the lumber; for right or for wrong, it’s how you’re initially gauged as to whether or not you’re a good golfer. Second, flaws in your swing are more easily corrected by technology put into the driver, as compared to your other clubs, so it makes you feel like you’re accomplishing something and gives you a false sense that you’re a good golfer; your irons, wedges, and putter all require increasing levels of finesse and accuracy, where technology is less able to help because a lot of this part of the game is the mental part. And third, because it’s the place where technology can help the most, the manufacturers supplying the technology market the hell out of it; if you build it, and advertise it, they will come.
And so it is with sales and the sales technology stack – a hyper-focus on a relatively small part of what selling actually entails…
A Crowded Playing Field – Near the Top
Today’s sales tech stack is creating hyper-efficiencies, but it’s not translating into hyper-effectiveness. Despite an avalanche of new technologies arriving every day, new sales methodologies being conjured up, and one-stop magic bullet solutions guaranteed to cure your sales woes, quota attainment numbers continue to fall or remain relatively flat year after year, win rates are flat, and sales leaders consider their teams to be less effective than they were five years ago[i]. Why?
If we look at where the vast majority of time, energy, and money is being spent in developing technological solutions to sales issues, it’s focused on top-of-the-funnel activities: Who should I sell to? How do I find them? How do I engage with them? How do I engage with them economically (i.e. virtually)? Three of the top four technology categories address the beginning of the sales motion, and one (E-Signatures) is creating hyper-efficiencies at the very tail end of a sale. Thanks to Nancy Nardin of Smart Selling Tools for sharing this data:
I suspect that almost universally, sales managers have driven and continue to drive their pipeline by primarily measuring activity (vis a vis outcomes); they expect sellers to engage in x-number of outreach activities (calls, emails, social media contacts, etc.), which then drives y-number of appointments, which then drives z-number of opportunities, and so on. The number of outreaches which can be done economically in a given time period speak to the efficiency of this process, and the conversion rates at each step speak to its effectiveness. While this process sounds reasonable, it doesn’t take long, especially in light of today’s technology, to demonstrate how this pre-2000’s mindset will rapidly — very rapidly — collapse on itself.
How We Got Here
Robotic process automation (RPA) is, as the name suggests, letting a machine do the repetitive tasks a human would do. The concept (although not the acronym, which is much more recent) has been around for decades, if not centuries, and has driven efficiencies in many industries. For example, in sales we’re all familiar with the dreaded “robocaller”, a machine which “dials for dollars”, essentially casting a wide net and calling hundreds or thousands of relatively random numbers, attempting to engage a prospect with a recorded message which includes a call to action and/or automatically redirects the person who answered to another machine or person. This is an efficiency play, where a known average number of telephone pick-ups are converted to secondary action. Make x-number of calls to generate y-number of follow-on activities to generate z-number of sales. And, since RPA could make calls 24/7 if desired, the number of sales is a statistical function of how many calls are made with a given number of autodialers – simple math. However, as conversion rates drop (people start ignoring unknown or blocked numbers, people switch from land lines with listed numbers to unlisted mobile phone numbers, etc.), higher and higher numbers of calls are required to maintain a given number of sales. At some point this becomes untenable and potentially damaging to a company’s brand.
Around the mid-80’s, the concept of sales development[ii] took form. Activity at the front end of the sales cycle — identifying, connecting with, and pre-qualifying leads — was offloaded by some larger companies from their sellers to other people (sales development reps, or SDRs), who would then set appointments for the sellers, theoretically freeing up the seller’s time to engage more frequently with their prospects and existing clients. Whereas a seller might spend a few hours each week engaged in outreach activities, a team of SDRs could do this for 40+ hours a week, in principle ensuring a constant pipeline of pre-qualified appointments for sellers. This practice is still employed today by many companies, either as an internal or outsourced function. The difference between this more modern SDR practice and robocalls is: 1) the list of prospects to reach is less random due to aggressive statistical market analysis, done either by marketing or artificial intelligence; and 2) people are able to pre-qualify prospects, filtering out the “cold” prospects before handing off the “warm” ones to the sellers. The better the SDR is trained in interpersonal communications and qualification of prospects, the higher the conversion rate and the more effective this process becomes. Of course, the seller still needs to determine if there’s a true opportunity present and further qualify (or disqualify, depending upon your point of view) this warm prospect before limited internal resources are committed to the opportunity (never forget we have to sell internally before we can sell externally). The benefit here is that the seller begins later in the sales cycle with a higher probability prospect.
Today and in the near future, AI may be on the verge of becoming as or more effective at pre-qualifying prospects as most human SDRs, which means at some point the ROI from AI will offset the ROI of SDRs (which is bad news for many SDRs). Where we were limited economically by, say, the 10 SDRs we could afford and their 500 outreaches each day, AI combined with RPA can now do thousands and fill that pipeline with far more pre-qualified leads than we could ever have imagined just a year or two ago! And look at all the great technology that’s available to help us do all these amazing things! It’s nirvana! What could possibly go wrong…?
The Efficiency Play
Here’s where this falls apart. Still pervasive in most sales leaderships’ mindset is a focus on activity, and that more activity is better; if, given the below-stated hypothetical conversion rates, 950 outreaches equals one sale, then 5,000 outreaches should equal more sales. We can surmise this to be the mindset because of the number of vendors which are flocking to create technology designed to improve top-of-the-funnel pipeline generation, which they wouldn’t do unless they saw a demand in this space (or unless they’re trying to create demand in this space). In many peoples’ minds, more is better and bigger is better, at least where sales is concerned.
But here’s the rub: How many meetings with new clients on average can any one seller manage in, say, a one-week time period? It will vary depending upon the industry, the seller, and the buyer, but for argument’s sake let’s say 10, considering they also need to work with their existing opportunities and clients. The sales tech stack is going to create dozens, if not hundreds, of appointments in a seller’s pipeline – most of which they’ll never have time to meet with. Today’s sales tech stack will likely create log jams at the appointment and meeting junction, with a scarcity of new technology to help sellers in the rest of the sales cycle. Plus, a meeting not kept by a seller turns into negative POVs about the company. The result: little to no movement at the bottom of the pipeline and brand erosion.
In true “more-is-better” and “track the activity” fashion you may be getting ready to say, “Just hire more sellers.” However, that tactic doesn’t scale well. The number of sellers you’d need, for the amount of activity today’s technology can potentially generate, might cause you to increase your salesforce by a factor of three or more; that’s an incredibly costly proposition, and the market for good sellers is highly competitive, especially considering today’s pool of available sellers probably isn’t large enough to support what’s already coming.
Another option is to insert sellers even later in the sales cycle. For example, create another layer of qualification (using people or AI) so sellers only deal with fully qualified opportunities, or allow clients to self-qualify (or self-disqualify) using branched marketing portals or buyer portals. Branched marketing is becoming more common in B2C (think about how you can configure and buy a Dell computer without ever interacting with anyone), but in B2B, unless you’re selling commodities, this may not provide buyers with enough resources to make a decision. CPQ (Configure-Price-Quote) [iii]software is another way sellers might get pushed deeper into the cycle; currently it’s an internal tool used by sellers and product teams, and if it’s placed into the hands of buyers then sellers could potentially be pushed down to the Closings stage, simply validating that the self-created solution meets the customer’s needs. The problem with moving sellers deeper into the sales cycle, however, is the missed opportunity to add value to an offering, which is a primary reason sellers exist.
What’s Needed: More Focus on Effectiveness
As important as efficiency is in the sales cycle, we’ve just demonstrated some of its limitations in scalability and impact, at least given today’s state of technology. What isscalable both today and in the future is an increased focus on improving effectiveness. We see that increasing efficiency by making more outreaches doesn’t increase the number of sales. Likewise, if we increase the effectiveness (conversion) of the outreach by leveraging AI to find better qualified pools of prospects and work with marketing to increase the impact of messaging, we still hit that log jam and fail to move the sales needle.
If, however, we focus on increasing effectiveness (conversion), we are able to move that sales needle:
Note that the suggestions for improving conversion involve cross-functional solutions, not just sales; impact to sales can be found throughout the organization. This holistic, systemic look at the entire business operation is necessary, which is why sales enablement as a function is increasing in scope and popularity.
The CRM Paradox
Given the prevalence of CRMs in the sales tech stack, I think we need to give it a bit more attention.
CRMs are an interesting technology and have grown in both popularity and functionality. Increasingly, CRMs are more than an “electronic Rolodex”; you might be better off thinking of them as an ERP for sales. Through third-party plug-ins and cross-platform APIs, CRMs can now offer content delivery to customers, function as a CMS to develop customized just-in-time and on-demand marketing assets, deliver targeted training to sellers, act as financial portals… Their core competency of Customer Relationship Management has morphed considerably, and they can now be a framework on which most things related to selling hang. But are CRMs a top-of-the-funnel tool? Largely, I believe the answer is yes, or at least it appears to be the main usage of the tool – which makes sense, given its DNA.
Two large issues with CRMs, which is by far the largest category of the sales tech stack, are adoption and data integrity. As to adoption, there seems to be a widely held opinion, and perhaps rightfully so, that a CRM benefits everyone in the company except the seller, yet the burden of the CRM is placed largely on the seller as to data entry and data integrity. Many sellers fail to see the ROI of their interactions with a CRM. Because of this, CRM adoption is driven through compliance with policy and the necessity of using the CRM to get paid, rather than because a seller is committed to its use as a useful and value-adding sales tool. The CRM/seller relationship is adversarial, and sellers tend to use CRMs only when necessary. Because of this, data integrity suffers, such as when a seller will sandbag deals and only enter data at the end of each sales stage, and sometimes only the absolute minimal amount of data at that. This can skew the effectiveness (conversion) numbers mentioned previously. Strides are being made to make CRMs more useful and appealing to sellers, such as by offering marketing asset compilation and delivery with handy feedback as to what was opened and how long the customer looked at one piece of collateral over another. And again, these tend to be more top-of-the-funnel applications. As CRMs evolve, and as corresponding technology evolves to automate data gathering and entry to take the burden off the seller, they may find more usage deeper into the sales cycle.
The pendulum seems to be swung hard over to the side of technology these days because of the speeds and efficiencies it offers and, as I’ve just pointed out, a focus on efficiency will only get us so far. Everyone’s doubling down on XaaS, Artificial Intelligence, and generally pulling people out of the sales function in more and more places. We need to remember technology is a double-edged sword; it can certainly increase efficiencies and reduce human-induced error, provided there is data integrity at the beginning of technological applications, and without data integrity bad data can blossom into a monster with tremendous destructive powers. We also need to remember that sales is still very much a human-to-human activity, and people are not machines into which we simply write a piece of software code and out pops a different behavior the next moment. Technology vendors need to examine how they can help people be better at their jobs, not replace them, because the value a human brings to sales, such as relationship building, intuition, morality, empathy, and the ability to work with other irrational human beings, is something technology can’t replace. For those of us working with sales groups looking to help them improve their performance, we need to pull that pendulum back toward the center and not always look to technology vendors for solutions; we also need to look at developing the greatest technology that is already at their fingertips — their people.
I’d like to hear more about what you are seeing and experiencing where technology in sales is concerned. Has the positive impact of technology hit a speedbump? Are we headed in the right direction? To what degree can technology impact mid- to late-funnel selling activities? Let’s keep the conversation going…
[i] CSO Insights. (2018). Selling in the Age of Ceaseless Change: The 2018-2019 Sales Performance Report.
[ii] Wikipedia. (2018, July 19). Sales Development. Retrieved from Wikipedia: https://en.wikipedia.org/wiki/Sales_development
[iii] Salesforce. (2019). What is Configure, Price, Quote (CPQ)? Retrieved from Salesforce.com: https://www.salesforce.com/hub/sales/what-is-cpq/