Getting Pricing Right

If you’ve got the power to raise prices without losing business to a competitor, you’ve got a very good business. And if you have to have a prayer session before raising the price by 10 percent, then you’ve got a terrible business. — Warren Buffett

What to do?

1. Define your customers — Build data driven profile of your customers — It helps in identification of the most relevant and lucrative customer segment on which one should focus. Pick less than half a dozen target buyer profiles with an educated guess, a gut feel. Write the name of the groups, what they value, what they don’t value and their willingness to pay. Also, put down what group, according to you, has the most revenue generating potential for your business.

Assign a persona to each group identified — Follows this pattern: [group attribute] [first name]. It helps to keep things intuitive. These are people, not numbers. Humanize your buyers. Assign descriptions — both demographic and behavioral — to each persona. They should have succinct definitions that are relevant to your organization. Like:

• Startup Susan — She’s pre-revenue or hits $1M in revenue. She’s not sophisticated with her processes yet, and is mainly focused on her core product.
• Mid-market Malik — He’s a mid-stage company that’s making $10M to $50M in revenue. He runs a team of 12 to 25 people.
• Enterprise Ernesto — He might generate $75M or more in annual revenue. He isn’t likely going to use the product personally, but will more often be a decision maker.

This description can go deeper. The objective should be that you and your team can recognize them easily in the field. Each persona would have its own value proposition.

2. Collect Data from Potential Customers — Good surveys lead to good pricing. Bad surveys beget bad pricing. Simple as that. If surveys don’t generate good data, it’s often due to user error. Without thought to incentive or user experience, it’s no wonder we get back bad results and lose faith in surveys as a tool. But, if done correctly, they can be very powerful.

To start, focus surveys to test two elements — features and price sensitivity — with a relative preference methodology. The first survey helps rank your core features to determine relative preference by customer cohort, and the second focuses on overall price sensitivity — essentially a customer’s willingness to pay for the product.

Feature preference surveys- Extract people’s preferences in only a few questions. Ideally, to test relative preference, ask two questions:

In two quick questions, you get the pulse of what’s most and least critical relative to other features that may be on your list.

It’s most effective to send surveys with 3–5 questions every three weeks, than a longer survey every quarter. Shorter surveys can generate responses at four times the rate — or greater.

One last point about relative preference questions: it’s vital to ask what they most prefer, not what they most use. Usage doesn’t always correlate to value. Note the features that they don’t really value as well. — Campbell

Take accounting software. Invoicing is typically the highest used feature, but workflow and practice management are often much more highly valued, because that’s the sticking point in their business. Just because a feature, like invoicing, is always present and used in a system doesn’t mean that it will be the differentiating feature.

Price Sensitivity Surveys- Two parts are critical — The first is your value metric or how you charge (e.g. per user, per hundred visits, per thousand views) and the second is willingness to pay, which helps determine threshold pricing.

For value metric surveys, use the relative preference methodology. If you’re selling an analytics product, you could do per user, per visualization, per gig of data or per integration. Let’s say you have those four options to test,” says Campbell. “ Set up a relative preference question with each listed as a choice. Send those to customers or prospects and ask, out of those four, where do you derive the most value from this product and where do you derive the least?”

Perhaps people don’t really care about users, but they do really care about the number of integrations and most of all about the amount of data flowing through. Eventually, this helps you map out how you’re actually going to charge. The implication for getting this right is if you get your value metric correct, your expansion revenue becomes less of an issue. All of a sudden your small, medium and your large customers naturally fit on a spectrum and you’re basically getting them at different points of value along a demand curve. Without this, you’ll end up charging Disney the same price as you’d charge Price Intelligently, even though we act differently on our preferences.

Another pitfall is blindly following traditional value metrics. Don’t do things just because they have always been done like that.

For willingness to pay, you’re not necessarily trying to get perfect price points. You’re trying to figure out what the price elasticity looks like. You never want to ask someone point blank: how much should this computer cost? human brains just don’t naturally understand the intrinsic value of an object. We know it’s worth across a spectrum. I know my computer’s more valuable than a pencil, so because of that psychological phenomenon, we should ask ranged questions.

• At what point is this way too expensive that you would never consider purchasing it?
• At what point is this starting to get expensive, but you’d still consider purchasing it?
• At what point is this a really good deal? (You’d buy it right away.)
• At what point is this way too cheap that you’d question the quality of it?

That last question is almost more important than all of the other questions because you’ll figure out your bottom limit. If you’re unsure of the stretch of your price elasticity, pick up the phone and call a few early or potential customers. “From those feelers or initial survey results, a ladder will start to form. You’ll see that a good deal for your product is $100 — which you could choose to optimize for adoption — and that you’re getting expensive at $200, which you could select to optimize for revenue. All of a sudden, you’re on the way to a deeper analysis, which will get more sophisticated when you get 50, 100, 200 responses to these four questions. But you’ll start seeing valuable, directional trends as responses trickle in.”

2 Approaches to launch Surveys —

If the issue is getting large enough sample sizes for each of your customer personas, there are a couple of companies that can help. “Instantly, formerly uSamp, Fulcrum and a few other companies provide market panelists, so you can get responses from a soccer parent in Kansas or a Fortune 500 CIO. If you’ve got a consumer product, there’s no excuse for not doing this type of research,” says Campbell.

If this still feels like too much of an investment, just start small — but don’t expect a to get a full picture of your customers personas immediately. “That may mean one question per quarter, starting with what’s most preferred out of five features. Then the next quarter you do the four questions on pricing. Then the next you ask about the preferences for annual versus quarterly versus monthly billing,” says Campbell. “Like puzzle pieces, all of these will add up over time.”

What you want to avoid is the sudden realization that you need to be charging five times more than you are and the mess of messaging this reality to customers. So bite the bullet early and do a comprehensive study or start rolling out a small set of feature and pricing questions every three weeks early on, ideally right after you’re hitting around $85K MRR — what Campbell sees as a good mark for product/market fit and the time to really start scaling.

Apply your findings — All the personas and surveys serve to fine-tune one key area: your pricing page.

Plot out price elasticity — It shows the demand for your offering changes as your price changes. Startups can use the data captured by the same four willingness to pay questions to plot an elasticity curve. Once you make those calculations, here’s what it’ll look like:

Behold, The Pricing Page!

Once you’ve mapped your price elasticity curve, you can now refine each buyer persona by their feature preferences and willingness to pay. “Now you have an updated sense of the value for and motivation to buy for each group. You knew theoretically that everyone is at a different stage, but now you can track tipping points,” says Campbell. For example, the very early-stage startup that wouldn’t pay $1,000 for a product that would solve a lot of headaches, may now, as a growth-stage company, see the value of that price for the time it’ll save. That’s why you need to collect this type of data over time — to know when Mid-market Malik’s willingness to pay is actually five times that of Start-Up Susan, which may change your entire strategy.

Few of the common traps to avoid from the beginning:

• Death by check marks. “Pages with columns of check marks delineating each package is the first sign of a pricing page that’s likely built on little buyer research. They’re often designed and organized with the products in mind, not the people purchasing them,” says Campbell. “It’s not typically intuitive what the material difference is between the tiers, which is a big problem if you hope to have a touchless or semi-touchless sale.”
• Mind your 9s and 5s. “There’s much misinformation on pricing out there. Common gimmicks dressed up as ‘pricing hacks’ include: End your prices in nines or fives. Or put the most expensive plan on the left instead of the right,” says Campbell. “Some of those techniques may make small differences, but are not substitutes for the basics and won’t generate more customers over the long run. Avoid micro-testing prices in lieu of more a wholistic process to build a pricing strategy.”

Use your customer personas as the foundation of your pricing packages. Remember those initial hypotheses on buyer profiles that you refined with customer surveys? Use those to build your different columns. Your customer should be able to go to your pricing page and understand the difference between each of the plans in under 20 seconds. Enterprise Ernesto should be able to find the enterprise plan, and self-correct quickly if he’s looks at Startup Susan’s package.

When to show or change your pricing?

Early on, many startups don’t want to show prices — and that’s okay. Most don’t really know what they should charge, so they prefer to get intel by asking inbound customers some pricing questions. However, when you reach a point where you either want a touchless sale, then you need to show your pricing. If it’s not a clear number, give a range. It doesn’t mean your pricing is negotiable — just that it varies depending on the customer.

In terms of adjusting pricing, the rule of thumb is to refresh it every quarter or two. A lot of people get nervous to change pricing because they don’t want customers to perceive that they’re paying more. The truth is that people understand that products cost money, but they need to get in a rhythm of how that changes as your product changes.

As you improve your product and add features, show that those changes correspond with an increase in value and price. “First, your recurring feature preference and price sensitivity surveys should help verify and justify price raises, so you’re not operating in the dark. If pricing is adjusted on a regular basis, it trains your customers to understand that the value is going to be changing as the product is improving,” says Campbell. “The worst thing you can do is add so much value over the course of three to five years — even 12 months — and then all of a sudden want a big bump from your customers who have gotten used to paying a specific amount. That shock is what leads to pissed off customers and churn, not necessarily the higher prices.”

In reality, there’s a lot of customers who are willing to pay more. “They just needed to be coaxed into it over time rather than one big bump. So what should you do? Every three to six months there should be changes, but you shouldn’t be effectively raising the price every three to six months on someone,” says Campbell. You should be able to say to your customers, we’ve done X, Y and Z. This is the effective new rate for this price and it’s a long-year value metric because we had provided more value. Some will say okay right away, most will consider it, and some will ask you to answer a few questions.

“Don’t make people pay more for what they have, essentially lowering their value metric. Add in a feature to the enterprise tier and get people to upgrade. Or introduce a related plan with a slightly higher value metric and price. Those are ways that you can effectively make sure you’re constantly evolving and optimizing your pricing.”

Whether it’s early and just the founders or you have heads of product, sales and marketing, whiteboard your potential customers into personas. For each profile, assign your hypotheses of their preferred and least preferred features, as well as their willingness to pay. Then test your personas with relative preference surveys — whether that’s on your own and quarterly with a few questions or with the help of companies that can offer market panelists. Apply your findings to create intuitive pricing pages so clear that your customers can see themselves in them.

P.S. The notes for this post are taken from Firstround.com as a part of my daily learning series.