Leveraging Data for Customer Insights & Sales Growth
Metrics are important, but metrics for the sake of metrics is a waste of your time. One client/s Business Development Manager was using a dashboard to measure all activities, including marketing. I was making a sales call on that client one day and the manager called me into his office:
“Why are you charging us $100,000 for this marketing activity?” he asked. I was surprised. “I assure you I’m not,” I replied. “I would know a number like that.” He said that his dashboard said it was true. I replied, “Again, I assure you, it’s not true. It’s clearly a mistake, but I can certainly check.”
I didn’t have to check. The next day when I was there making the rounds he called me in and apologized; apparently, his accounting department has mis-allocated a charge from a construction database to our account with the client.
In another instance, a client had hired a major PR firm for social media. Using their metrics, they armed the CEO who went to the corporate headquarters with metrics that should a significant increase in followers. When presenting to the corporation, the CEO was challenged on the number, because the corporation – a multi-national corporation – had been tracking their activity with their own global agency. They had different numbers – much lower than what the CEO was showing. The PR agency had been “cooking” the metrics, which can be easily done depending on how you “count” followers.
These kinds of stories exist when companies plunge head-first into metrics and rely on dashboard instead of real-word information. As Jim Mattis the former secretary of defense said in his book Call Sign Chaos, “Digital technologies can falsely encourage remote staffs to believe they possess a God’s-eye view of combat. Digital technologies do not dissipate confusion; the fog of war can actually thicken when misinformation is instantly amplified.”
I used to be asked continually how many leads were a good number? My answer was always the same: one, as long as it was the right one. For example, it depends on the average selling price of a product. In B2B, with two-step distribution and value chain participants like architects, engineers and contractors, it is rare you can metric where or how a lead turns into an customer. Besides, how do you define “customer?” There are so many different factors that affect the B2B journey. So the key is to try to measure as much as you can, but have an understanding that a lead-turning-into-an-customer can come from unexpected places. Here are some key metrics to consider.
Customer Acquisition Cost (CAC): How much you spend to gain a new customer. This time-proven metric while difficult to find is a good indicator for your lead generation purposes. Along with the next lifetime value, you should know what it costs you to acquire someone. In B2B, it’s not a linear path. Acquisition costs are everywhere and should include all expenses your business incurs to attract, engage, and convert a prospect into a paying customer. Some of them include marketing and advertising costs, sales team costs, lead generation costs, CRM and other technology costs…in other words, pretty much your entire business. The fact is, your entire team should be focused on new business!
If a company spends $50,000 on marketing, sales, and lead gen and gains 200 new customers, then: CAC=50,000/200=$250 per new customer
It sounds easier than it is. Direct marketers use response rates and conversion metrics as well. Just do your best at figuring out as close as you can your costs for acquisition.
Customer Lifetime Value (CLV): The projected revenue from a single customer. The math is fairly straightforward:
LTV = Average Purchase Value × Purchase Frequency × Customer Lifespan
Where:
Average Purchase Value (APV) = Total revenue / Number of purchases
Purchase Frequency (PF) = Total purchases / Number of customers
Customer Lifespan (CL) = Average number of years a customer remains active
But this involves RFM analysis – Recency, Frequency and Monetary. And, depending on the business or service, lifetime can be defined differently: a real estate agent might measure lifetime value of a customer very differently than Wal Mart does. It really depends on how granular you want to get.
In B2B it is especially challenging because you have to define “customer.” For example, if a manufacturer who has a specified product going into buildings, is the architect who specifies the product a customer? The engineer? The distributor? Practically, you should follow the money. When I first got into the business and learned about these value chain participants in a specified product, I asked my client: who pays you money? The answer, of course, was “the distributor.” And this particular client had 1500 or more distributors. Running life-time value calculations on that dataset proved interesting and worthwhile. However, none of that would have occurred unless the product was specified in the first place. So the architect, while never purchasing anything, became a target for the calculation and the equation changed:
LTV = Average Specification Value × Specification Frequency × Architect Lifespan
This required careful study of specifications for the firm. Then, it led to an entire campaign of architect acquisition (going after firms that specify a competitor for example).
The point is that such metrics drive speculation and inquiry which often lead to new paths to gain and keep customers!
Engagement Metrics: Click-through rate (CTR), time on site, bounce rate. These are rarely helpful in our opinion. We heard a major executive for a digital firm once say, “HITS is How Idiots Track Success.” Hits are nice to know, but not a need to know. That therein lies the different in understanding your metrics…to decide between the nice to know versus the need to know. Click through is nice to know (though some will argue it’s a need). Only you yourself can decide which is which.
For example, take phone calls. There are plenty of metrics you can have for engagement on the phone. There’s the win-loss ratio (how many nos before you get a yes), time per call, etc. But engagement on the phone is often determined by not only the goal of the call, but the ability of the caller to create empathy with the target. I’ve had people working with me that can engage with a professional for over a half hour, when the goal was a couple of questions. The insights gained from such encounters can’t be quantified in many cases.
To illustrate, in a research project on restrooms in airports to determine whether or not they are using IoT technology, we interviewed numerous facility people who run them. More than one told us this: “Technology is not used in our small facility and no consideration given to the technology.” Even in a larger facilities we heard repeatedly, “They utilize QR codes. Visitors can scan the code to communicate an issue.” (who does that?) We engaged in extensive conversations, averaging over 30 minutes with over 50 people. Two clear groups clearly separated themselves: larger airports, and smaller ones.
In these discussions, what became apparent was this: “IoT” wasn’t a concept that understood enough to make judgments to use or not use by the facility itself. Larger facilities outsourced the function, making the janitorial service the primary, while smaller ones “did restroom maintenance manually themselves.”
No clear benefit” for IoT was heard multiple times to the question of how the technology might help.
Our client had the opportunity, therefore, to redefine IoT! To do that we recommend a blue ocean/red ocean strategy: by side-stepping where the competition is fighting right now to create the blue ocean where there is no competition. In this case, the smaller airports.
Our recommendation was to create a “concierge” type IoT service for small airports, where the client installs their technology to “proven the point” at little or no cost to the facility itself. The Federal Aviation Administration (FAA) estimated that there were around 14,400 private-use airports and 5,000 public-use airports in the US. Smaller, private airports are frequented by high-end consumers. These consumers “talk” to each other about their experiences – restroom and otherwise. If more and more of these airports and smaller stadiums utilized our client’s IoT, more and more people would talk about it. It could only have come about from engagement, but the “metric” had nothing to do with it: conversation did.
Grabbing a bigger share of the market in the red ocean is a zero-sum game – that is, one company’s gain is achieved at another company’s loss. But in smaller airports, it was all our client’s to gain, since competitors were looking elsewhere.
Retention Rate & Churn: Measures how well you keep customers engaged. Again, this depends on the “type” of customer you are engaging with. Retention can mean “life long” value, or in some cases, how long they stay on your website.
For example, using reverse IP lookup technology, we can tell when an architectural firm comes to our client’s website, what they “look at” and then cross reference it with projects they are working on from another database. This gives the sales person a laser-focused target to hit with an appropriate sales call. We can then see how often (retention or churn) they return to the client’s website. Based on their journey, we can tell if they are considering the “right” product for the project we calculated they are working on. Retention, in many cases, becomes close to 100%. And when drops do occur, we can do a phone call to see what changed.
Social Media Sentiment & Engagement: Shows brand perception and audience interaction. Many companies like to increase followers, but followers are they increase seem to lessen engagement. There’s just so much time in the day! Our recommendation is to take note of these types of metrics, but not get bogged down into follower counting.
Keep reading our series on How to Target and Hit the Right Customers: Deep Dive Insights.