Editor’s note: Joe Procopio is the Chief Product Officer at Get Spiffy and the founder of teachingstartup.com. Joe has a long entrepreneurial history in the Triangle that includes Automated Insights, ExitEvent, and Intrepid Media. He writes a column about startups, management and innovation each Monday as an exclusive part of WRAL TechWire’s Startup Monday package.
Thus blog is the fourth of a four-part series. The previous two posts are embedded in this column.
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RESEARCH TRIANGLE PARK – Are you going to hit your revenue targets this year?
There’s never been a worse time to have to answer that question, but there’s never been a better time to create more predictable revenue forecasts.
The key to solving the forecasting puzzle is, of course, establishing a consistent and growing run rate. In other words, if your revenue target for the next 12 months is $1 million, your focus is on a consistent number of $83,333 per month, every month.
But no business has consistent revenue — unless of course they have recurring revenue. That’s the pot of gold at the end of the traction-and-scale rainbow, and subscription pricing models seem like the natural means to those ends.
One problem. As I wrote recently, subscription pricing doesn’t work for every product or service. Subscription models only make money in cases where the customer’s demand cycle fits the timing of the subscription model.
Most products and services don’t fit that model. So what do you do?
I’ve got over 20 years experience building, selling, and especially pricing products and services to get to traction and scale with recurring revenue. Here are five alternatives to a subscription model that can encourage repeat business.
If you have customers, you don’t need machine learning or big data to start predictive marketing right now.
Put simply, predictive marketing is sending your customers a reminder of your product or service before they need that service, and good predictive marketing gives them a reason to act. That reason could be an effective message, a discount, or just good timing.
Basically all you have to do is get one of those right.
If a subscription pricing model encourages customers to buy based on your schedule, predictive marketing encourages customers to buy from you on their schedule. It’s much easier for your forecasting model to conform to the customer’s actual usage patterns than the other way around.
The catch is you have to know a bit about your customers, and you have to document and act on that knowledge. This takes work, but a good automated email service can handle all of the actual emailing for you if you spend some time with it.
You’ll need to understand some of the habits around the use case for your product or service, and you’ll need to understand the habits of your individual customers.
If you’re tracking when your customers buy, you can make some guesses about the next time they’ll buy — which you’re probably doing anyway if you’re doing any kind of legitimate forecasting. If your customer has only bought once, your guess is based on your product’s general use case, and then you learn from those guesses as you go. Then tie all of that work into an email marketing program or level up and do it right there in your app by sending notifications.
Over time, these random guesses become educated guesses, with data to back those guesses up. This makes forecasting much more accurate.
Normally the domain of retail businesses, I’m always surprised that more companies, especially startups, don’t implement a loyalty program.
The goal of a loyalty program is right there in the name, but the purpose of a loyalty program is to create additional touch points with your customers. This allows you to do some additional opt-in marketing, messaging that they’ll be expecting and probably read and maybe act on. It also allows you to activate them with deeper discounts when you need to prioritize revenue over margins.
The process is to give the customer a reward for future business. But the benefit to you is that you’re saving about half the cost of acquiring a new customer. So be generous with what you’re giving. Remember, loyalty is expensive, so make it worth the customer’s time.
A loyalty program doesn’t have to be complicated and moreover it shouldn’t be. Don’t make the customer have to keep up with your program via an app or God forbid a paper card. You track their loyalty for them, with their email address or phone number, and make the reward automatic. I’d also recommend against complicating the program further with points or stars or thresholds. Pick a discount, make it achievable and worthwhile.
Once the program is in place and you start getting knowledge about its influence, you can generalize this knowledge to make better guesses about future sales.
A lot of entrepreneurs will confuse loyalty and referral programs. This is probably because, unlike subscription models, loyalty and referral programs work for just about any business or offering. However, loyalty and referral programs have completely different goals.
While loyalty programs focus on getting more revenue out of existing customers, referral programs are built to reduce the cost of bringing in new customers. The former is about increasing Lifetime Value (LTV), the latter is about decreasing the Cost to Acquire a Customer (CAC).
Both programs can target your best customers, as they’ll be your most loyal and your most-willing to refer others. And that’s where the mistake is made. Because the goals of the programs are so different — LTV vs. CAC — they need to be rewarded differently as well.
Loyalty is about discounts, referrals are about commissions.
Thus, your target for a referral program isn’t necessarily your best customer. In fact, your target for a referral program might not be a customer at all. It’s someone who has access to large groups of potential customers. For certain businesses and offerings, the target may indeed be your best customers. For others, referral targets should be people like market experts, influential bloggers, or group administrators.
Think of your referral team as a random, secondary sales force. Reward them handsomely when they bring in a new customer who ultimately generates revenue. If your referral team is made up of your best customers, give them more product. If they’re not, give them commissions.
Both referrals and loyalty programs are easy to experiment with and mold to fit the needs of your offering. Unlike subscription pricing, which has to fit a certain model of customer demand, these programs shape themselves to that demand. Tweak them and improve them over time as they get results. Then use the results when forecasting.
Any single sale of multiple units can and should be easily discounted. To take advantage of this, make that discount known up front.
Tiered pricing is a great way to do this, and you can tinker with a tiered pricing program in ways that can make your forecasting more accurate. The only problem is that messing with tiers requires messing with the offering itself, whereas all the other methods are layers that sit on top of your offering.
You don’t want to change the tiers too often. So how do you get it right the first time?
- The first tier is your basic sale, a single unit or engagement, maybe priced a little higher than you normally would, in order to entice the customer to buy ahead of schedule.
- Your second tier maximizes the customer value proposition. This is the tier that will satisfy your normal recurring customer use case.
- Your third tier maximizes the value of the recurring sale to your company. This is your power-user customer, the one that was going to buy in bulk anyway.
Now, apply that strategy to your own offering. If you want to add additional tiers or include variability, remember to give a much higher discount for the more units sold in one sale. Remember all that CAC savings when pricing.
Call this customer success, a concierge, guided onboarding, dedicated support, whatever makes sense for your business. Turn that into a program, and fold in retention and upsell initiatives.
For higher-dollar sales, a customer advocate is a requirement. The role helps the customer find value in your product, keeps the customer satisfied, and looks for opportunities for additional or repeat business based on the customer’s individual needs.
It’s basically all the other programs wrapped into a job function.
- Your customer advocate checks in with the customer when they believe the customer might be ready to buy again.
- They reward loyalty with the authority to discount.
- They ask about potential referral opportunities.
- They proactively suggest additional units or a move up in tiers.
Obviously, this is the most expensive option, as it requires at least one full time resource. But if you do the retention and upsell parts right, the role can pay for itself many times over.
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Previous posts in this series:
Startups, subscription pricing & risks: It’s not an easy opportunity
Startups, subscription pricing & you: How to make the strategy pay off
Secret weapon for startups: Embrace subscription pricing – here’s how