HomeUncategorizedMaking Big Data Work for B2B Sales

Making Big Data Work for B2B Sales

Retail salespeople always seemed to have it a bit easier than B2B salespeople: the price is on the tag, take it or leave it. Traditionally, they haven’t had to experience an arduous sales process that entails the nerve-wracking procedure of coming up with a number based on the potential customer’s budget, obtaining the customer’s reaction, modifying the price on the spot, and then keeping fingers crossed that the customer accepts a price that not only closes the deal but also yields a profit for the vendor.

But times are changing. As a recent New York Times headline put it, “More retailers see haggling as a price of doing business.” With access to more data than ever before, consumers are more sophisticated and educated. Historically, consumers relied on the salesperson for education.  Now, with the Internet at a shopper’s fingertips, this is rarely the case. Customers know the value of their business. They only need to scan the barcode of an item to see which stores are selling an identical item, and for how much. This data emboldens them to walk up to a sales associate and say, “I see this item is on sale at Amazon for 20 percent less. I’m going to go buy it on Amazon unless you can match that – right now.”

With mobile price-check applications and information literally in the palms of their hands, shoppers are now in the driver’s seat, and they are not afraid to haggle in stores. While retail companies are just starting to train their salespeople to address the customer about to walk out the door, B2B companies have been dealing with this delicate pricing dance for decades.

Money On the Table
If price negotiation were indeed a dance, B2B salespeople would consider themselves prima ballerinas. But it’s not time for B2B sales to feel complacent about their expertise, for two reasons. The first is that field sales does not always get the pricing dance right. Too often, sales reps prepare their own quotes based on an intangible read of the customer, and they frequently determine the closing price without detailed guidance. They’re relying on instinct to maximize profit without jeopardizing a deal – but studies show that predictions based on “gut feel” are accurate only about 40 percent of the time. This means it’s likely that despite their experience, sales teams are either leaving money on the table or losing profitable customers.

The second reason is that business customers, like retail consumers, are increasingly taking the lead in this dance because they are now better informed and more savvy than before.These days, purchasing agents are typically more than half-way through the buying process before they call in sales. They knowwhat competitors are offering. They know what to ask for, when to walk away and where they can get a better deal.

Salespeople must have information to counter buyers’ negotiation tools, and they need it on demand at their fingertips. They need to know what price the customer has in mind and what’s included in the other companies’ prices in order to negotiate from a position of strength. That’s just the start. While it’s not difficult for salespeople to do their research on competitive offerings, it’s far more complex and arguably more important for them to know the relationship between the price they give and the profit the business will gain. According to a recent study by MIT Sloan Management Review, “pricing has a substantial and immediate effect on company profitability…small variations in price can raise or lower profitability by as much as 20 to 50 percent.”

It’s almost impossible for a salesperson to accurately predict profitability based on instinct alone because it encompasses potentially dozens of variables. These variables range from volume to shipping charges to seasonal demand and inventories. Salespeople can’t manually calculate all that data to arrive at the best initial ask price and the walk-away price on the spot. Nor can they maximize profitability unless they have all that data, distilled down into very clear pricing guidelines.

Just as consumers now have smartphone apps and purchasing agents have software to run comparisons, field-sales organizations can now level the playing field by tapping into the latest pricing-optimization technologies. These encode corporate experience into algorithms and apply them across massive data sets – an organization’s Big Data – to yield predictions of customer behavior and projections of profitability.

B2B sales will always demand a certain level of art and emotional intelligence. The same can be said for B2C sales. But it is possible to take the guess work out of B2B sales. With hard numbers backing their decisions, salespeople will be able to stand by prices with confidence, just like retail salespeople used to.

Joe Boissy is Chief Marketing officer at Vendavo, a leading provider of Big Data analysis tools, price management and optimization solutions to companies worldwide.

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