Beyond Product Effectiveness, Cost Saving Insights for Brands Found in Real World Data

Who hates coming across unexpected costs with your business?

The answer is everyone.

If you aren’t collecting the right information on an ongoing basis, it’s likely unexpected costs will eventually surprise you.

Here’s how we helped a brand identify one of these surprises. And how you can avoid it.

It comes down to the value of Real World Data, beyond proving product effectiveness.

We worked with a brand who wanted to collect data on how effective their product was for appetite suppression.

The data came back overwhelmingly positive for their product. Many different data points, from close to 100 individuals who used the product for a month, found the product was effective in reducing people’s appetite levels and improving eating habits.

On the final day of the month-long campaign we asked each individual to leave a 1-2 sentence product review. We ask this so we can see what people think/say about the product in addition to what the data says.

You want the reviews and data to say the same thing. If the reviews say something different from the data, you likely need to do some further investigating on both.

That was the case here.

Most of the reviews matched what the data told us about the product.

However, there were a few reviews from people who claimed the product “didn’t work”.

To have a few people out of 100 say the product didn’t work isn’t abnormal. Rarely do you get 100 people to agree on something and have the exact same experience.

However, these reviews provided more context. They didn’t just say the product “didn’t work”. They stated a specific reason for why they said the product didn’t work.

Those reasons were either “I didn’t lose any weight” or “I didn’t lose enough weight”, therefore the product doesn’t work.

This was interesting because not once did we mention anything about weight loss. We made sure to stay away from that language and instead focus on Appetite Suppression.

So why were people saying the product didn’t work for them because they didn’t lose enough weight?

The product name directly insinuated you would lose weight if you used this product.

So even though the data collection focus was Appetite Suppression, everyday when people used this product they read the product name, which made them think they would/should lose weight just by using it.

Even with the data showing their appetite levels went down, because they didn’t lose weight (like the product name suggested they would), they thought the product was no good.

We called this to the brand’s attention when reviewing the data report with them.

They were grateful for the in-depth insights and feedback.

This resulted in the brand changing the name of the product, how they marketed it, and how they educated consumers about it, to better set and manage expectations.

A change that wouldn’t have happened if they didn’t collect Real World Data from consumers on the use and performance of their product.

Without this data, the product name would have stayed the same, and even though it was effective, a portion of consumers wouldn’t have converted into repeat customers because they had the wrong expectation.

Compounding Benefits of Real World Data

This one data report provided the brand with:

Real World Data that found their product to be statistically significant in helping reduce appetite levels and improve eating habits.

AND

Insights to inform a product name change to improve consumer experience and retention.

Incredible ROI.

In the data report we found another important marketing/consumer education need that we shared with the brand.

Many individuals who participated in this month-long campaign said one of the reasons they used this product was to help reduce the frequency of late night snacking, or grazing.

Which makes sense. Late night eating is a common eating habit most would like to kick.

Two results in the data report pointed out something that could be problematic for this use case.

The data showed statistically significant evidence the product was effective at increasing people’s energy. There was over a 30% increase in reported daily energy levels while people were using the product. And, more than 50% of individuals Agreed with the statement that they noticed an increase in their energy after using the product.

These two data points were further supported by a few reviews from people saying the product kept them up at night because they used it too late in the day.

By pulling together and cross referencing different data points, a product education need and opportunity was discovered that would (again) improve the consumer experience. And, decrease the chance of a consumer having a bad experience with the product.

Start Collecting Real World Data

These are insights you wouldn’t receive from traditional consumer market research.

This is the unique value of Real World Data. It’s also an example of the compounding benefits that come from collecting Real World Data.

Luckily for this brand, it wasn’t a huge deal to change the name of the product and adjust the marketing. But there were still costs. They had to:

• Design and print a new label

• Adjust the name on all digital and print marketing content

• Create new content to market the product

Yes, these are expenses that could have been avoided if this data was collected when the product was launched.

Incorporating a Real World Data campaign into a product launch, or (even better) a pre-launch, strategy not only helps you better position your product when you do bring it to market. As detailed above, it can save you from unexpected costs down the road.

However, I’d bet that whatever it cost the brand to make those changes was significantly less than what they would have missed out on in repeat customers. This change will lead to a higher repeat order rate and greater customer lifetime value.

This isn’t only relevant for medical focused brands, or brands who are trying to validate product effectiveness.

It’s for brands who want to make sure they are the most informed with their product marketing strategy. And for brands who want to avoid surprises down the road.

In this example, nothing was “wrong” with their marketing strategy or the product. The data showed opportunities to improve marketing, and increase repeat customers.

Something every brand owner is trying to do on a daily basis.