Tag Archives: buyers

How Sales Reps Can Do More To Differentiate Their Product Offerings

In a recent posting, technocrat blogger Geoffrey James has taken on the topic of differentiating roughly commoditized offerings. He summarizes the winning options facing sellers of identical products as thus:

“There are five other differentiators that you can put into play which will keep the customer buying from you at a higher price.  They are:

  1. Convenience. If your product is easier to purchase than the competition’s, the customer may pay more for it.
  2. Tradition. If purchasing your product is a well-established habit, the customer may pay more for it, at least for a while.
  3. Perceived Quality. If your product is perceived to be better made, the customer may pay more for it (even if in fact it is identical).
  4. Your Personality. If the customer personally likes you, the customer may be willing to pay more to keep you “on retainer.”
  5. Mutuality. If you are involved in a partnership with the customer that’s crucial to his business, he may pay more for your product.”

All of the options on this list are viable ways to get your product (or keep your product) in the customer’s hands. Certainly, brand-driven values, such as “Tradition” and “Perceived Quality”, are a very real reason for customers to choose a good. Of his other options, “Your Personality” and “Mutuality” are roughly approximate to “Relationship value”, both leading a buyer to stick with a given seller. And I tend to agree with his closing sentiment that “’Convenience’ is the one that’s the most powerful (and the most commonly neglected by sales professionals).” But again, that is really part of the product offering (meaning they weren’t truly identical in the first place).

Unfortunately, if you don’t already have a relationship with a buyer, most of these options (other than “Convenience”) won’t be as available to you. Moreover, you will likely be on the other side of some of these options, looking in.

One differentiation that he may have left out is the ability to build expectations in your customers without an existing relationship. While charm is one (possibly antiquated) way to do this, an easy way to elevate your pitch is to avoid the product offering completely; instead, tell the buyer what you know about them. With more information available every day, a fast way to breed confidence in your customers and elevate your brand is to show what you know about their environment, challenges and goals, and implicitly their needs. When you prove you know what a client needs, you become trusted, and can help them make a product decision, rather than keeping them from going with the known quantity.

A simple analogy exists in Internet radio. There is a glut of online music options, but with a growing number of what I’ll call ‘intelligent stations’ (such as Pandora and Grooveshark). These are ones in which your past listening preferences determine your future playlists, based on a combination of data being gathered on your listening patterns and explicit preferences. While they are playing ‘exactly what you want to hear’, all they are really doing is telling you that they know what you like. In particular, you will end up choosing the one that “knows you the best”.

In the same way, if you, as a seller, can read back all the things you know about what your buyer is seeing day-to-day, your recommendations will have much more weight; even if you are proposing the same good as your competitors.

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Predicting Customer Behavior in B2B

As the CEO of Lattice Engines, I frequently visit our customers and prospects to talk about how they can use predictive analytics to improve the performance of their sales teams. Some of my most interesting conversations have been with analysts inside these organizations, usually very smart Ph.D’s in Operations Research, Economics or the hard sciences, often with a background in B2C direct marketing.  A common lament I have heard in these meetings is that while they have tried to build recommendation models for their sales teams, gaining adoption (and respect) has not come easily. As one analyst eloquently put it, “In my B2C job, a lift from 1% to 4% would have made me a hero, whereas to a B2B sales rep – there is no difference between 1% and 10%.”  So what makes predictive analytics for B2B different from B2C?

In our experience, the difference lies along five dimensions.

  1. Customer hierarchy: Target entities, i.e., the businesses that you are trying to sell to, have internal structure. Just saying that “Wells Fargo” is a good customer for a particular product is not helpful to sales reps; they also need to know which “Buying Location” is likely to be a good candidate, and within that which contacts are likely to be good candidates.
  2. Product structure: Products are often configurable, complex and have internal structure. Unlike a consumer product, say a book or a piece of clothing, a business product can often be sold in multiple configurations or as solutions comprising of multiple SKUs. A model built at the SKU level would be useless to a rep because that’s not the unit in which they make their sale.
  3. Sparse data-sets: The time-scale of commerce for most B2B businesses is months to quarters. Trying to find patterns at a level below this does not make sense, as it would for a B2C ecommerce site. However, aggregating data to this level creates its own problems. Even if you have 4 years of data, and the customer transacted half that time, you only have 8 data points to train on. How do you “learn” from a sparse data-set using statistical techniques that assume a dense data-set?
  4. Multidimensional data:  One of the positives of the B2B world is that there is a massive amount of data available about customers and prospects including attributes (e.g., Employee count, Revenues), triggers (e.g., recent CIO transitions), product usage (e.g., call-backs, logs) and customer interaction history (e.g., CRM, Transactional systems). The combination of sparse data with multiple dimensions creates the curse of dimensionality, and modeling approaches need to take this into account.
  5. Incomplete, Inconsistent & Dirty Data:  Different data-sets used as training parameters have different levels of cleanliness. For example, CRM data is notoriously dirty because it is entered manually by sales reps who would rather be out selling. Similarly, data from Marketing Automation systems is often inconsistent and unreliable because it does not respect customer hierarchy (see point 1), and is often built off purchased email lists. While these data-sources are very useful, any predictive model must recognize their limitations.

Since the ultimate consumer of this information is a very motivated but skeptical human-being – a Sales Rep – the bar for clarity and correctness is much higher in the B2B world. Simply porting standard statistical models from the B2C world tends not to work so well.

At Lattice Engines, we are investing heavily in making B2B sales reps more effective through the use of data and analytics, and have built our products (salesPRISM sales intelligence software and playMAKER marketing intelligence software) to overcome these challenges of providing accurate predictions for sales teams. Our models are cognizant of the unique characteristics of different types of B2B products (e.g, configurable, services, transactional etc.) and selling models.

Are you part of a B2B analytics effort? What has your experience been?

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“Don’t Bring Us the ‘Dog and Pony Show”

Once upon my career, I was a B2B buyer and met with sales reps on a regular basis.  Much like a salesperson’s time, my time was limited. To maximize meetings, I did the research upfront.  Before the salesperson walked in the door I already knew what they were selling, what it promised, who was using it and how they liked (or didn’t like) the product.  But all too often, a salesperson would come in and spend half of our meeting telling me and my team things we already knew.  They’d prepare elaborate presentations with beautiful graphics, hand out promotional items, even bring in baked goods.  Despite the clear effort they put into producing what they, the sales reps, felt was a great meeting, we, the buyers, left the meeting with questions unanswered, forcing us to have yet another meeting and extending the buying cycle.  And so, at the request of my boss, the following term started making its way into our communications: “please don’t bring us the dog and pony show.”

B2B buyers want to know why your product or service matters to THEM – how do you serve their immediate and future needs?  B2B buyers are looking to shorten their buying cycle, which will help you shorten your sales cycle.  To make the most out of meetings with potentials buyers, sales should focus on three points:

  • Ask open-ended questions before the meeting. Buyers know you can’t read their minds.  Ask them what they’re looking for or what problem they’re trying to solve.  If you come prepared to talk about “everything but the kitchen sink” you may never get to what they actually need.
  • Apply context and relevancy to your messaging. Research the customer to find out what’s happening in their organization, how it is affecting their part of the business and specifically what you can do to help.
  • Leave the ‘dog and pony’ show at the door.  An elaborate presentation may catch a buyer’s attention, but it may also distract from the sale.  Stay focused on the customer’s needs and how you can help them.
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