Traditional CRM is outmoded, says Brian Kardon - so it's time for predictive CRM, something that will take sales from art to science.
The world was a very different place 25 years ago. There was no internet. There was no email. And mobile phones were the exclusive property of the wealthy (who also required significant upper body strength to use them).
It was into this world that CRM was born, in essence little more than a contact management system.
Even 15 years ago, things were still very different than today. The internet was still in its infancy. Email was still gathering momentum. And mobile phones were still strictly for phone calls.
By this time, CRM had gained customer service and support functionality and sales force automation, but at its heart it was still its contact database.
Spool forward to 2012, and the question is whether CRM has evolved sufficiently to keep pace with the changes that have taken place in the wider business landscape.
One person who is not convinced is Brian Kardon, former chief marketing officer of Forrester Research and marketing automation vendor Eloqua, and current CMO of Lattice Engines
, who believes that CRM has become a “dated technology”.
“Salespeople do a lot of research now outside of CRM, because all CRM really has is a name, address, contact information and – if it’s a really good system where salespeople have used it – the contact history. CRM is kind of like an electronic rolodex and salespeople can go into it and order their accounts alphabetically or by sales revenue,” he explains.
“It has been around for a while and has not really kept up with the pace of what happens in a modern selling environment. Sales people now go to lots of different places for information – they go to LinkedIn to see what they have in common, they do searches, they read an article, they go to security statements about the company and read the annual report, and then maybe into some other database…”
Big Data, big challenges
Indeed, salespeople have never had so much information at their fingertips – something that at present is both a blessing and a curse, according to a survey of over 200 CEOs, CSOs and sales executives by Lattice Engines and CSO Insights.
This report found that while over a third of respondents had implemented technology to bring internal and external information to sales reps, with win rates around 8% higher than companies without the technology, still over 80% admitted they felt challenged by the amount of data available.
Nonetheless, while only 16% of those questioned had Big Data strategies for sales at their organisations, 71% of those who knew about Big Data could see its potential for aiding sales.
“Before they call a customer, the average rep checks 15 different sources,” says Kardon. “They spend more and more of their time doing research, looking for a needle in a haystack. But we believe you can automate that now and that sales can move from being an art to a science. So we’re finally at this tipping point where we have enough data to do it.”
The product of this is something he calls “predictive CRM” – a system that pulls together both internal and external data about prospects to predict which accounts are more likely to buy.
Lattice works so that within a system such as Salesforce.com, Microsoft Dynamics or Oracle, a salesperson is able to see their accounts ordered by the probability that they are going to close, and by clicking on the account they are also told what to mention during a call and what the trigger items are. These trigger items could range from, for instance, the company opening a new office, or having undertaken a new round of funding or having landed a new government contract. Furthermore, the system also highlights other similar accounts, by industry, size or other parameters.
“It is modernising CRM from being a flat database, to being very helpful in telling sales reps who to sell to and what to talk to them about,” adds Kardon. “But the other important thing is that we don’t overwhelm sales people with thousands of pieces of data – it all sits behind a curtain, and only those pieces that are most relevant to the phone call are presented with that account.”
And while adoption has traditionally been a challenge for CRM, the nature of predictive CRM ensures that if salespeople understand it will ensure that they are calling the right accounts at the right time instead of wasting time in front of the wrong customers, they should take a very different attitude towards it.
“CRM is not built for the rep, it is built for the management,” continues Kardon. “Companies employ CRM to get visibility into the pipeline or to enable forecasting and while there is lots of value for management, there is almost no value for the rep using it. We think that with predictive analytics, the rep will want to use it because it helps them close more business.
“We can monitor usage and reps are using it like crazy. And the reason that CRM is now being used a lot in these organisations is that before it almost like a punishment for them – they had to put all this information into it and there was no benefit for the rep – but now they want to use it because it actually tells them who to call and who to avoid.”
New salespeople are particular beneficiaries of this system, able to reap the rewards of what Kardon calls the “democratisation of sales excellence”.
He continues: “Your best reps are the ones who have been there a long time, they know who to call, they have good intuition. So we’re able to take that good intuition and good with data and the systems around it so that even a new rep will know who to call.”
Those already embracing this predictive slant on CRM include Lattice clients such as Dell, HP, EMC, Adobe and Microsoft, businesses that Kardon characterises as “the most sophisticated B2B sales organisations in the world… the early adopters”.
But while he believes that this demonstrates there is no question that it is becoming a competitive advantage for some of these big organisations, Kardon also concedes that not everyone is so keen on this new branch of CRM.
“The most common objection we get is that it is a lot of work,” he explains. “We have to pull data from the internal databases and from external databases, we have to train the salespeople… so when we find a sales leader who has been there for a long time and is risk adverse and doesn’t want a lot of change, he is really not a good prospect for us. However, when we find a really bold sales leader whose GDP is only going up 1-2% this year and whose target is 6%, and who understands that there is no way he can get there if all he does is hire more reps and provide the same old training, then that is the kind of leader who wants to try something new and will embrace predictive analytics.”
For the time being, Kardon believes that Lattice is the only vendor operationalising Big Data for sales reps, but he does foresee a time when predictive CRM could become more mainstream, and actually be baked into standard CRM systems. The next generation of CRM? Just possibly. However, this is likely to still be some time off yet.
“Right now, it is separate from CRM,” he suggests. “It really depends on what the CRM guys do. They might just decide that their systems aren’t built for it or that it just isn’t a big enough opportunity. Marc Benioff at Salesforce.com certainly has a lot of other things he’s working on, so I’m not sure where it’s going to be. It could be that companies like ours will build the analytics and then we plug it into CRM, or it may be that CRM companies decide they want to do it themselves. The jury is out.”
What Kardon is certain of, however, is the value that predictive CR M offers to the rep, the sales department and ultimately the business.
“We’re starting to see early adopters use predictive analytics not in an academic way, but in a very practical way. Companies like Dell and HP are all in very competitive categories and are looking for a competitive advantage and they’re finding that if they can apply predictive analytics to their sales teams, they are finding great results.” He concludes: “It is a flag for other organisations that these big successful companies are doing it – it demonstrates that it is something they ought to look at too.”