Platform Native
The idea of an omnipotent software platform and the evolution of Customer Science go hand in hand. Customer Science is the upshot of my idea that we’re in the process of converting from random acts of CRM in the front office to a more structured, efficient, and predictable approach to conducting front office business. Platforms make Customer Science possible.
The emphasis on collecting and analyzing customer big data has taken up most of the brain space in the discussion about the front office but it is only half of the Customer Science story. The other part is what vendors do with the information they distill from customer data. They might simply use a fragment of analysis to tell customers that other people almost like them bought product B when they bought product A but that’s like carpet bombing when a laser guided approach would work so much better.
A better approach to the new vendor customer relationship implied by Customer Science is to use the information to first construct journey maps and metrics and to then put in place business processes mediated by powerful software that leverages all of the new kit that’s come to market over the last few years, in short the platform. That includes workflow, social, transaction oriented analytics, and mobility solutions for starters. All of these specialized components have to be part of the underlying platform on which the solutions rest. Thus platform has become a big deal.
Platform is arguably much more important than the messaging surrounding it might suggest. The vibe I get from the messaging is that platforms are cool and, well, don’t you want to be cool? That’s early market messaging, the kind of thing that vendors spout when the use case is still being fleshed out, but platform is already much more than this.
In reality, if the Customer Science light bulb shines brightly above your head, platform is essential for the simple reason that the modern, Customer Science driven front office can’t possibly write by hand all of the software you’d need to support a single business process across desktop, laptop, iOS, and Android let alone integrating apps from Salesforce, Oracle, Microsoft, and SAP. Thus platform has become the new application table stakes for our industry and making apps on platforms that are open to the rest of the universe is a business necessity.
The big attraction of a platform, at least one constructed properly in my humble judgment, is that for the most part it exists a level above raw code and that it can generate the code for the business process on all of the platforms that a business wishes to deploy — one specification for all user interfaces the business is likely to need from the handheld device to the desktop.
Additionally, a platform, rather than the application, should be the point of integration with third party apps so the platform must be able to support apps working together whether they are all written natively or they come from widely different sources. The capability to do all of this was once science fiction but today’s leading platform vendors make it look easy.
From a business perspective, it’s a game changer. Software companies (and most other companies) have always sought out ways to lock in customers. Prior generations relied on compilers and database standards to carry that load with the result that getting applications to simply exchange data was viewed as reason to celebrate. No wonder it has always been so difficult to string together multi-vendor support for common business practices.
Platform is bigger than all that and one example of its impact is the Force United Consortium a group of vendors with applications built on top of the Salesforce1 Platform. They include Apttus, FinancialForce, and ServiceMax among others. Their extra value add is that their disparate applications not only integrate well with Salesforce products but that their solutions are almost indistinguishable from Salesforce and each other at the foundation level because they are platform native meaning they use the same objects from the Salesforce toolkit. Of course, they do vastly different things too and that’s the point.
The consortium elevates the members as well as Salesforce to the status of an uber application, sharing data but even more importantly sharing metadata that supports the business processes on a common platform that make Customer Science possible.
We’ve come a long way from the times when computer automation was mainly about making data more accessible to better support manual business processes. Big Data gave us the insights to understand customers in ways we never could before and platforms are enabling process automation not simply data storage and retrieval.
There are still things that only people can do in this highly automated environment but the new science and platforms make the people involved in the processes much more productive and importantly they provide better and more intimate association with customers. Ironically, process automation is still not widely accepted, it is only gradually becoming part of the landscape though of course, leading practitioners have already gotten and digested the email. Perhaps next year it will see greater emphasis for the rest of us.
Importance of the Journey Map
The journey map and the tools used to make one might be the sleeper part of CRM in the year or two in front of us. The reason is simple, journey maps enable you to figure out your processes and they are useful in much more than just marketing.
Recently in this column I’ve discussed the emerging science of the customer, which is probably not the term that will ultimately stick in anyone’s head. But the key element of the idea is that the random and highly reactive approach to front office business is rapidly being eliminated because big data and analytics are showing us where the opportunity clusters are and where we shouldn’t spend our precious time.
There is a virtuous circle nature to this. We need better processes because our analytics tell us rather convincingly what our customers think is a waste of effort and those things that we really ought to pay attention to. But knowing the things is not understanding process. A customer might want an end result but it’s the vendor’s obligation to deliver all the things that lead up to the result a.k.a. the processes.
Take customer onboarding as an example. It’s an idea familiar to a lot of us but how many of us take responsibility for it? There’s glamour in sales, less in marketing and once the customer crosses what we consider the finish line, too often that’s it. But customer onboarding is the most important part of the whole relationship, other than securing the John Hancock because it builds the relationship.
Onboarding can include everything from getting the product out of the box and registered to correctly entering your metadata. The point is that every business has a set of rituals that must be observed but too often there’s no high priest. Maybe there should be since onboarding is one of the key moments of truth that a vendor-customer relationship has.
Not to get too far down a single path, but onboarding is just one example of a customer journey that looks like a dotted line dirt road on your map and that’s where journey mapping becomes important. There should be zero dirt roads and vendors need journey mapping to plan out all of the possible ways a customer can take a wrong turn so that they can make the situation right well before frustration sets in and bad things follow.
So journey maps are really important in marketing because we want to establish an absolutely fool-proof path from interest to closed deal just as we want to get the product out of the box and a smile on the customer face. You might recall when I introduced the idea of customer science that I likened it to a form of sociology whose major point of interest is how societies erect structures for people to work within. In sociology the opposite of structure is agency as in taking responsibility for going it alone. When customers carve their own paths too often bad things like attrition are the result that’s why structure is so important.
So you can look at the journey map and its supporting tools as the business’ structure making socio-customer-science effort to keep revenues flowing in one direction and customer happiness percolating in the other and that would be a good thing.
Journey maps will be found all over your business in a few years, starting with marketing’s effort to corral customers to sales’ attempt to get them branded, but there’s more. We’ve looked at onboarding already but I think the biggest impact journey maps will have will be in service and support. Currently too many businesses have one or maybe a small handful of service and support processes and few specialists. That’s about all you can have with manual processes or dirt roads in this parlance.
But at worst, a business ought to be able to segment services and support into maybe 8 or 10 service processes each with its own specialists and SLA. A how-to request might come into the same place as a request for enhancement but the two ought to take very different trajectories from there. Currently that’s too manual and mapping these separately might be the first step to speed up both and deliver greater satisfaction.
In doing that mapping, we’re finally able to concretely describe the engagement we want in ways that don’t sound like an ad for a new vitamin. Better still, and this is huge, we can ensure that the end result of the engagement is not an accidental hang-up or worse.
Some people might say, well, that doesn’t happen any more but if you think that, you’re just not getting involved in the vendor-customer give and take enough. I got thinking about all this recently when I called my local gas and electric utility to report a dead tree hanging off some power lines like a barfly on a barstool. I made the unwitting mistake of getting to the gas side of the house rather than the sparks.
The very nice and efficient person on the line told me she couldn’t help me and couldn’t even transfer me. Worse, the website behaved as if it was designed by whoever built Fort Knox and I repeatedly bounced off. All I could do was send a DM to what I thought was their hash tag along with an editorial comment on the efficacy of their service solutions. This being Twitter I had to compress it all into one word.
Had this energy company thought through its moments of truth and built its journey maps rather than operating a very efficient customer service site circa 1995, things could have been different. The point is that we’ve trained customers to reach out to vendors in various ways but we are still receiving in manual mode. Time to create journey maps that will take us to the next level.
More Front Office Science from Xactly
Xactly continues its pioneering ways by analyzing anonymous data collected by its customers in compensation management. If you aren’t familiar with the company or its groundbreaking market analysis, you might be in for a treat. Their appr oach is relatively simple but extremely powerful. With the permission of the data owners, Xactly strips out identifying information and conducts sophisticated analysis of sales compensation practices looking for patterns. The result is revealing because it comes from a very large data sample and it is corrected for potential bias and error.
The company’s first effort revealed a small but real pay gap between sales reps based on gender with women earning less as is the case in much of the economy at large. Interestingly, women in sales stayed at their jobs longer than their male counterparts while out performing men by about 3 percentage points both as individual contributors and as leaders. Nonetheless, women were paid less in both base and variable compensation than men. Lastly, women appear to be better leaders than men and they build sales teams equally composed of men and women while male leaders’ teams were mostly male.
Ok, that’s the gender gap. Xactly’s next analysis compared sales rep compensation across regions of the US dividing the country by time zones — Eastern, Central, Mountain, and Pacific — they found that sales people in the Central time zone received the highest base pay/variable pay mix as a percentage but were only third out of four in ranking their total compensation, despite having the highest average quota attainment of all regions at 82 percent. In stark contrast, average quota attainment in the Pacific, Mountain, and Eastern zones was remarkably consistent at 66 percent, 69 percent, and 67 percent respectively.
For Xactly’s purposes this is very useful because it helps sales managers and others to compare how they compensate their reps vs. an industry average. But more broadly speaking, it would be nice to be able to drill into the numbers to a higher degree.
For example, what is it about the Central time zone that drives sales performance that is on average so much better than other zones? My hypothesis, which could probably be proved with greater access to data, is that larger territories and fewer reps could provide better hunting prospects in the central zone but that’s just speculation. We don’t know if territories are richer in the Central zone but if they were it would suggest the attainment vs. opportunity ratio might be more congruent. And to the point, if attainment vs. opportunity can be so much better in the central zone, does it mean that the other zones might be over populated with reps? Having this kind of information drives all sorts of hypotheses that could improve performance.
Luckily, Xactly has more data than it is publishing for free and it is providing deep dive analysis to subscribers of a new offering that’s designed to help managers at all levels to better manage their businesses. This is a great example of unforeseen opportunity inherent in Big Data. Prior to Big Data, one could speculate but never know these answers unless one wanted to conduct an expensive in-depth analysis of data collected especially for such an effort. But with all the data Xactly collects, suddenly this kind of analysis is virtually free and the insights are extremely valuable.
More importantly, this kind of activity is happening all over the front office as more vendors take to analyzing raw data. Generally speaking we can point to before conditions that lack data and analysis and that relied on hunches and heuristics and if that’s true then the after condition has to be labeled science and that’s a big deal.
We’re living in a new era in which front office business is transitioning before our eyes from art to science and it is driven by Big Data and analytics. We saw it happening in the back office decades ago as paradigms like ISO9000 and Six Sigma made precise, high-quality manufacturing a numerically based and repeatable thing. But manufacturing takes on more of the quality of physics while, in my mind, the front office is taking on the character of sociology — as it should.
People after all have free will and the essential question of sociology is how social groups are organized to enable decision-making whether by structure or by agency. Structure, as you might guess, says that people behave in predictable ways because a social group is organized to funnel people toward desired behaviors. On the other hand, agency suggests that people empower themselves to go out side of established structures to behave in different ways. Life is full of both.
Xactly’s efforts so far say that structure is fairly uniform throughout sales culture with minor exceptions. Somehow it is apparent that the compensation structure is consistent and skewed against women. Also, remarkably there are regional differences as well in the structure of compensation plans for all sales people. Equally significant it appears that women take agency in slightly different ways than men, for example, staying at their jobs almost a year longer. They may nurture their direct reports better possibly accounting for greater performance as managers and apparently they are doing something better as individual contributors too.
There are bound to be differences between groups when we do this kind of analysis and the purpose is not to expose anyone’s behavior as “wrong.” The purpose is to use data and science to identify opportunities to manage better and Xactly’s insights into base and variable compensation do exactly this.
