Month: January 2016

How Bullhorn Pulse Steps into CRM’s Future

I’m impressed. I just finished readingbullhorn pulse logo U.S. Patent 9,189,770 Automatic tracking of contact interactions. This was recently granted to Bullhorn, Inc. for it’s “Pulse” sales acceleration technology. The patent and the product point to the same future of CRM I am evangelizing here at SALESPHASE.  We differ in that Bullhorn Pulse is a magnificent step, versus SALESPHASE’s one-order-of-magnitude greater leap, into CRM’s future Bullhorn Pulse provides an automated data analytic method of analyzing actual customer interactions to get a clearer picture of which deals are winning and which are losing.  It uses its own patented remote access to contact tracking technology to automatically add a copy of any detected email message to the activity records of the sender and contact within the Bullhorn CRM system (or other CRM if I read the technology correctly).

I think Bullhorn Pulse advances sales pipeline technology in three important ways:

  1. Automated, which for me means reduces wasted time, unnecessary effort and the potential for mistakes;
  2. Analytic, which for me means it relies on measurement and not manager or sales rep guesses;
  3. Qualitative, which for me means that it can interpret its measurements to determine which deals are simply “a bunch of activities” and which are “customer engagement.”

I agree completely with the co-founder and CEO of Bullhorn: “Sales activity reporting is dead,” Art Papas has stated, “Lots of activity and no engagement equals no results – we’ve learned this from listening to our customers over 16 years.”  Art’s insights resonate deeply with my past experience as a sales rep, account executive and business development manager. It is the same basic reasoning that lead me to found SALESPHASE.

Now that I’ve read the patent, I will start thinking about interesting ways to integrate Bullhorn’s Pulse technology with the advanced never-before-seen methods SALESPHASE will use to extract intelligence out of far-from-perfect information. Bullhorn Pulse analyzes specific customer interactions which it detects as relevant, such as an email to or from a customer.  SALESPHASE is what I call a deal characterization technology.  It provides a higher level of intelligence and feedback about deals without relying on guesses or any particular communications with customers: it doesn’t look at any specific mode of customer interaction and doesn’t care what the deal is actually about or what the buyer and seller’s internal processes look like, etc.  It is independent of any specific context and therefore it can stand on its own or play well with any established CRM system, whatever suits the user.  You might think, how is that possible? Follow me on Twitter @salesphase and keep an eye on for the beta test signup.  –John Clark


Overthrowing Newtonian Sales Thinking

Newtonian Sales CRM is Old School

Without knowing it, the sales component of typical Customer Relationship Management systems–even the most advanced applications available–remain sadly and securely rooted in Newtonian thinking.  SALESPHASE is changing that by throwing out the fundamental axioms of sales acceleration technologies and replacing them with new thinking, new math and new algorithms hidden completely behind an ultra-simple user interface and experience.  But that’s getting ahead of the thought train I’m trying to conduct here, so first let’s go back a few hundred years to Newton.

Newtonian thinking includes in its most fundamental principals the following logic: Given perfect information at any point in time (initial state) we can predict what will happen at any future time (final state).  Of course this is theoretical, because we rarely have access to perfect information.  But my experience with CRM and sales acceleration applications over the past 15 years has been witness to a continuous striving towards “perfect information”.  Technological progress with respect to the Internet, smartphones, data collection and analytics feeds right into the Newtonian paradigm of seeking the illusive fountain of perfect information.  If we can know exactly what our customers are thinking, planning and doing we could (in theory) custom design a marketing and sales strategy for each customer.  This was impossible a decade ago, but technology today allows even huge companies (with the requisite resources) to nurture a sense of one-to-one relationship with customers.  This is why I’m invested in Marketo for its digital marketing technology designed to provide real-time engagement with customers whether by email, video, social media, etc.  But digital marketing is not always the answer, especially for high-value long sales cycle products and technologies. SALESPHASE is aimed squarely at complex sales where the cost of getting to the deal phase with a customer is substantial.

I do not dispute that the better our information is, the better our actions based on that information will be.  But there is a marginal cost associated with moving to the next level of “better information” in your business, whatever that might be.  And as information increases, gathering, storing, analyzing  and finally using it gets more complicated and costly.

The Cost of Perfect Information is Infinity Dollars

I think we can agree intuitively, without any formal proof, that the marginal cost of better information approaches infinity as we approach the limit of perfect information.  This implies that perfect information is both functionally and theoretically impossible to obtain.  This is no breakthrough in sales thinking or information science, but acknowledging this problem allows us to ask if there is some other fundamental principal or principals which could take sales metrics from an 18th century basis to a 21st century basis?  Well, we don’t even need to go that far.  We can stop in the early 20th century to find an appropriate new axiom:  between 1905 and 1915, Einstein abolished our scientific pursuit of perfect information in fixed space and time, and replaced it with the philosophically challenging but wonderful uncertain universe of “the quantum” (at small scales) and the flexibility of space and time at large scales and high momentum.  What could this possibly mean for sales acceleration applicatons?

Background Independent Selling

While Newtonian sales is about pursuing perfect information, Background Independent Selling is about extracting actionable knowledge out of far from perfect information.  I call it Background Independent because it can be implemented regardless of ANY differences between sellers, buyers, products, technologies, industries, etc., (all of such things I refer to collectively as “the background”).  For more context on what I mean by background independent, go here to read how the background environment is a source of sales friction.

So MUCH of the data that is pumped into sales CRM applications is highly specific information, but so what?

  • Is it accurate?
  • Is it useful?
  • Is it cost effective?

I have designed, implemented and used sales CRM applications across multiple companies over a 15-year period and, for the most part, I’d say the data is spotty, full of mistakes, and rather useless.  Marketing people would still call my mobile phone looking for customer information and insights, and my manager just looked at sales numbers and bugged me for answers if I weren’t hitting targets.  Sale reps who repeatedly hit targets were let off the hook on their sloppy CRM data, and poor sales reps were lashed and then tied to their laptops to spend hours logging data to prove they were working.

After implementation, I found CRM systems would take on a life of their own…they had to be FED and became the master instead of the servant.  CRM including sales-related components is implemented from the top down as a tool of management, not a tool that makes sales people better at their job or one that eases their job so that they can spend more time with family (or in the field).   I can’t think of any company that has EVER implemented a CRM process that its sales force found to be invaluable.

Failure to Launch

Recently one of my colleagues was attending a conference of business aircraft owners.  She was seated for dinner with a CEO who remarked that he’d spent a fortune implementing a major enterprise CRM system for his sales force only to s#^%-can it months later.  One can often attribute these failures to lack of planning, substandard technical implementations, insufficient training, or poor promotion of the new system.  But in this case, the primary issue was a complete lack of buy-in from the sales force.  In my opinion, the CEO’s complaints were unrelated to whether it was SAP, Oracle/Siebel or Salesforce; so I’m not going to name names here.  But I’ve worked with all three and know that the problem was platform-independent.

Three Reasons Sales People Despise CRM

No need to reinvent the wheel: I agree with John Holland’s May 2015 blog article, Three Reasons Sales People Despise CRM. (Read. Learn. Sell.)

  1. Salespeople ask or wonder WIIFM (What’s in if for me?);
  2. One size does not fit all transactions; and
  3. Entering CRM data is time consuming and doesn’t match deal flows.

I think these reasons require no further explanation, but certainly, please follow the link to the article if you wish to dive deeper, or read my earlier blog article on The Trouble with High Tech Sales Tools.


The main impetus for starting SALESPHASE has been to resolve the three reasons sales people despise CRM.  SALESPHASE is not a standalone CRM.  It does operate as a standalone sales acceleration tool,  but I see it as a complementary addition to existing CRM applications.  SALESPHASE objectives are as follows:

  1. Sales people happily exchange what they are currently doing for SALESPHASE because the benefits will show up as soon as the app is started and without any training.  If the rep knows how to use his or her phone, that all the training required;
  2. One size actually DOES fit all, it’s background independent;
  3. It vastly reduces data entry because most of the data collected before was useless anyway;
  4. It doesn’t lag or even match deal flows, it gets ahead of deal flow by extracting subtle key information that is usually lost in the noise; and,
  5. It generates measurements that allow comparison of sales rep performance, deal risk and probability of close regardless of the size of the deal.  More importantly, it exposes the probability that a deal is accurately reflected at the right position in the sellers pipeline.
  6. It distinguishes very early on which deals will be simple and fast from those that will be longer and more complex.  This allows proactive sales resource allocation and reveals potential hidden problems before it’s too late to solve them.

I will discuss the details under nondisclosure, but please bring someone from your team who possess a PhD in mathematics, as well as a solid mathematical programmer—not a coder.  Email me: john at sales phase dot com, or tweet me @salesphase.