‘can a rewards program increase revenue and profit?’

To keep a longer story a little less long, the answer was ‘yes’, but here’s a link if you want to see it in full. (You should totally do this for this follow-up to make perfect sense.)

Naturally, the feedback that came out was “awesome, this is the best advice, but what about ‘how to improve measurable revenue and profit with a rewards program’?”

Well, I’m going to answer that today. To start, let’s have a little refresher.
In part 1, I gave a little bit of theory – highlighting ‘switchers’, ‘loyalists’ and ‘detractors’.

1. Loyalists | they love you & your product, they’ll tell people about your offering and not wait for a sale to purchase
2. Switchers | they jump back and forth on products, typically based on offers and sales
3. Detractors | they only buy your product when it’s deeply discounted

In that piece, I said, but don’t quote me on this…, that switchers are where the money is at if you truly want to drive profit through a program. They require spend or, at the very least, activity, but don’t expect the earth, they’re pretty fair-weather people; that’s why we call them switchers.

Remember, profits from a program is all about winning the battle for the switch.

“Get to the how!”

Well, I always aim to please.
Here are two examples of how IC Group made it happen.

1. Identifying jump-off points

A client of ours in the diaper industry, who were trying to own the new-born to toddler customer journey, had a problem. It went a little like this:

• Parents would join the client’s program and enter a ton of codes. Perfect.
• But they would then mysteriously move across to trial a competitor’s diaper when it came to time for the next diaper in the journey, crawlers. Not so perfect.

Guys, this is so common across any program and is often left untreated, which is annoying as it’s actually a relatively simple problem to try and solve.

How we made it better

Our client had to react strongly in such a pressurized marketplace. We analyzed where the jump-off point truly was, aka where our client was losing most people in the purchase cycle, and made an educated decision (note: I said ‘educated’!).

Part of the answer was in media. This client began a campaign that let parents know they were THE brand for dealing with leaks, they made it a point across their entire marketing plan. (see our piece on entanglement as to why this is vital).

But there had to be a CTA to match the PR activity. So, we created an offer, based on analysis of purchase data as it related to abnormalities in the purchase cycle time frames. We identified the perfect moment to send potential switchers a high-value that included additional bonus points in their rewards program. This helped to hugely stifle the trial exodus.

Why did it work?

We utilized information to identify a risk point in a purchase cycle and rewarded heavily prior to consumer trialing – from free product trial to points, to rebates to content. We amplified the messaging as much as possible.

And the offer was two things, enticing but most importantly, it was timely. The above covers the enticing part, but we made sure the message was received the month before the expected date to change diaper styles. This meant we were getting into the buyer’s mindset at the critical time they were about to make their decision, typically a time when heavy media by the competition would be visible

While this worked, I guarantee that some of you are going to be thinking – “Kelly, I don’t have the budget for media!”

Well, here’s another example.

2. Sky rockets in flight, surprise and delight

That’s right, surprise and delight, in a rewards program! OK, enough rhyming…
With another client, what we did here was an instant win program to help combat a problem with program activity dropping off.

How we made it better

Again, we looked at data and different trends – web activity, purchases, shares, logins, uploads etc. You name it, we kept an eye on it.

We tracked all of these actions per member, aggregated back to the beginning but most importantly over a smaller subset of time where we would consider behavior to be accurate. If you were doing one level above just logging in, sharing on social as an example, we classed you as a ‘good member’ in our system. As soon as login rates, the real first inference of interest and activity for us, dropped off, offline activity and member scoring dropped too! To get these folks back, we went with a simple, but extremely effective, surprise and delight campaign.

It was as easy as this – ‘hey, we’ve not seen you in a while here and you’ve not scanned a receipt or entered a code, to get you back into the groove, we’d like to give you 500 bonus points’. All this was, really, was utilizing engagement data and having automated thresholds that triggered responses when not met, as a pullback strategy! As switchers are so changeable in nature, it’s pretty common for them to dip in and out, so this tactic worked a charm to reel ‘em right back into the conversion funnel! This minimized the time the switchers were “out” gaining back significant revenue and profit.

Why did it work?

Switchers are motivated by incentives. This one was down to pure enticement.