This is a guest post from Patrick Campbell of Price Intelligently, curators of an excellent blog all about pricing strategy.

Google "customer service" and you'll find dozens of freshly published articles every day of the week.

There are thousands of books on Amazon's shelves discussing the importance of caring for customers, and millions more tweets harp on good and bad experiences purchasing everything from consumer packaged goods all the way to some of the most boring B2B products in existence.

Thus, it's safe to say that service is on the minds of millions and is an integral part of doing business today.

However, this day-in, day-out discussion of customer service often skews toward making the practice seem more like a required expense on your spreadsheet, rather than a unique opportunity (and a profit-driver for your business).

Interestingly enough, after observing a few hundred thousand pricing studies at Price Intelligently, we started to notice that the customers of our customers known for phenomenal service appeared to be willing to pay much more than the customers of competitor products.

Of course, in the world of data, "noticing" something means squat until you run a test, so that's what we did, and that's what we're going to show you today. Spoiler alert:

Great service correlates to a higher willingness to pay by customers.

To better understand this, let's first briefly go through the tools we used to measure value before revealing the impact that phenomenal customer service can have on your bottom line.

The Tools We Used to Measure Value

For this study we utilized our two main value-based pricing tools to measure price sensitivity and relative preference. Both work by asking current or prospective customers a series of standardized questions that we've developed from several economic and statistical models. The data is then crunched through our algorithm and we get the output you see below.

Digging a little deeper though, the crux of both tools centers on utilizing the lens through which human beings think about value. For pricing, that means rather than asking a prospect point blank how much they're willing to pay for something—a question that's intensely difficult for the brain to comprehend—you ask several ranged questions (at what point is this way too expensive, at what point is this so cheap that you question the quality, etc.).

Pricing study

On the preference side, those of you who have ever tried to prioritize a feature roadmap know that asking customers what they want next in a product is met with a hearty "everything." That's why you need to force the respondent to make choices between different features or options by choosing both the most and least important of a group.

(For a more detailed walkthrough, check out this post where we ran a fun pricing study comparing the price of a lunch with Dharmesh Shah or Jason Calacanis.)

Pricing study

Customer Service Is Key

With our tools in hand, we wanted to test the hypothesis that better customer service correlates to a higher willingness to pay for a product. The problem in testing this, though, is you need to find a commoditized, common product to control for value fluctuations. After all, if we tested the price sensitivity for a designer scarf or an exceptionally specific enterprise software suite, we wouldn't be able to control for the variation in value perception.

As such, we turned to two common items in competitive spaces: a pair of The North Face E-Tip Gloves that retail for between $35 and $50, and a standard user seat for a helpdesk that retails for between $15 and $30 per user. To set the stage, we put together market panels of respondents who were target customers of some of the biggest brands selling these products: Nordstrom, Bloomingdales, Zappos, Amazon, etc. for the gloves and Zendesk, Help Scout, UserVoice, Freshdesk, etc. on the helpdesk side. All had purchased a product from the store in the past 6 months (for the gloves) or were current customers (on the help desk side).

We then presented them with their item (the gloves and the standard helpdesk seat), asked them the core pricing questions for that item, and then asked how they rated the level of service from the company on a scale from 1 to 10. The results were pretty sweet.

Long story short, customer service matters. Across the board we found a correlation between a higher customer service rating and willingness to pay.

Essentially, happy customers were willing to pay more in both the e-commerce and SaaS spaces.
Pricing study

These results may seem intuitive from an e-commerce perspective. Yet, on the SaaS side, they're of particular interest, because customer service isn't something we necessarily think about as a top priority in the world of software, at least in the aggregate. Feature prioritization, product development, and marketing all typically trump putting forth world class customer care.

Granted, great customer service is plentiful in software, but you don't hear examples of such as much as you do in retail, with the exception of great stories like Zappos ordering customers a free pizza during a support request, or Nordstrom accepting used tire chains from a customer who obviously bought them elsewhere.

Pricing study

Everybody wants to claim that they're wowing customers, but the nature of SaaS makes this difficult. Your goal is to get them through the door, and the nature of the recurring revenue model tends to lend itself to a path of least resistance in just trying to retain that customer through a basic level of care.

That's all well and good, but as these results suggest, getting your customers in the door and then continuing to wow them will not only help with your retention, but it will offer you an opportunity to supercharge one of the most important metrics in your business—your customers' monthly recurring revenue (MRR). Of course, you need a product to upsell them with, but that's for a whole other blog post.

You Can Differentiate Service

What's fascinating in the hundreds of pricing pages we look at every month is that most SaaS companies attempt to use support as a differentiator within their tiers. Free customers may need to rely solely on web documentation and maybe a user forum. Low-end paying customer may get access to email support, and then enterprise folks might even get an account manager. Although this flies in the face of the notion that you should offer world class support across the board, we've actually found that data suggests this is a good strategy.

In the age of dismal cable company and telecom support, a swell of certain customer segments is beginning to look for premium support options. Others (myself included) are okay waiting for an email response or in a call queue to get help when needed. This points to an impressive revenue opportunity by truly differentiating your support.

To test this, we ran a relative preference campaign amongst the helpdesk respondents to see what kind of support was most important to them. One of the more interesting slices of the data was by customer size (displayed below). Notice that customers with larger accounts really wanted priority support (pushed to the front of any line) or a dedicated account manager.

Smaller customers cared more about email and phone support in general. This all intuitively makes sense, because if I have 30 seats with a helpdesk company and something goes wrong with all of them, it's affecting a lot of people and I need help right away.

Pricing study

We're not saying that you should take support away from individuals on the low end, although that definitely is an option if that path fits with your brand. Rather, this type of data combined with the other studies points to a perfect setup that combines a phenomenal base level of support with some premium support features for those customers who seek out dedicated account managers, 24/7 support, etc. Obviously, the ideal makeup will depend on your customers and what kind of support team you want to cultivate in your company's culture.

Patrick Campbell

Patrick Campbell

Patrick is co-founder and CEO at Price Intelligently.