Design Thinking for Innovation Reflection    Adigun Okoro April 2020

Testing a Niche Market

A Learning Launch Reflection

The Challenge

Background; West African diets are traditionally high in carbohydrates.  Modernization is  increasingly making the foods more highly refined and abundant, causing a steady increase in dietary  problems, particularly obesity and type 2 diabetes.  There is a growing awareness of healthy eating  in the affected communities.  A nutritionist has developed a series of substitutes for the problematic  traditional foods and needs a compelling proof of concept to raise capital for the business.  The  formulas have been tested, tasted and don’t require separate FDA approval as all ingredients are  approved.  Production either requires the huge outlay of building a factory or outsourcing to an  existing factory with milling and mixing capabilities.

The challenge was to establish the commercial viability of this series of products.  To do this, I  worked with the nutritionist to test the assumptions that people of West African descent, who are  interested in healthy diets, would buy this new and unique product just because of the health  promises it made and that they would do so at prices that would be profitable.

Selection

I chose the Learning Launch tool for this challenge as it seemed to best fit the bill.  A Learning Launch  experiment to produces results fast and cheap and as we learned from the Frank in the video, to test  key customer execution and defensibility assumptions was ideal for the challenge.

Application

With the tool selected, I analyzed the assumptions and distilled them down to a simple “must be  true” which was “people will buy this product online at this price.”  There were some researched  factors, the cost of production and minimum order sizes were taken from outsourcing quotations.   The cost of advertising was estimated from quotations by a selection of advertising firms, the  advertisers chosen anticipated an average 0.5% response  The production and advertising costs were  added to anticipated admin costs and used to calculate production costs which was then multiplied  by a safety margin and marked up for profit giving us pricing for the experiment.

A simple webpage was set up, with the product available to buy and an initial mailing list of 1000  potential customers were emailed with an advert and a link to the sale page.  The mailing list  thousand were randomly selected from 20,000+ existing (opted-in) subscribers to the nutritionist’s  blog.  I played the role of a sceptic as everyone else involved was very excited and I wished to  mitigate the confirmation bias. After discussion, the sample customers were estimated to be ten  times more likely to buy than the unqualified leads expected from outsourced advertising.  This led  to an expected response of 5% (10 X the 0.5% provided by advertisers) to prove the hypothesis.

Upon landing on the sale page, customers were able to select items, review the shopping cart and  click ‘Buy Now’.  As the product wasn’t actually available to buy, and we didn’t want to take money  during the experiment, once the customers committed and reached the checkout, they were shown  a message saying that the product was out of stock and if the customers wished, they would be  notified and sent a discount voucher when it was available to buy.

Insight

The Learning Launch was a great success, the results of the experiment were very conclusive.  There  were 132 ‘sales’ from the 1000 prospects approached, representing a 13.2% percent response, far  above the 5% predetermined as a success marker.  As the sole success criterion was already  predetermined, further data analysis was unnecessary but the high response led us to project  returns on the full available (opted-in) mailing list of blog subscribers and this projection added  conviction to the decision to go ahead with the next phase of using outsourced manufacturing  production and starting online sales while building a case for scaling up to a purpose-built factory.

From my point of view, the assumption that the blog subscribers were ten times more likely to buy  than other members of the demographic, as well as the original projected 0.5% provided by the  advertising firms as an average response rate were nothing more than guesses and as such  represented a significant risk, but the relatively low cost of the Learning Launch phase 2 mitigates  this risk very well.  There was a financial decision made as the blog subscriber list was free and there  would have been a cost to using commercial advertising at this stage.  In the event that the  experiment yielded borderline results, we had pencilled in plans for a phase 1.5; running the  experiment again with a small investment in advertising.  As it turned out the results were  comfortably above the cut-off and this phase was scrapped in favour of going straight to phase 2.

Approach

Despite the success of the experiment, I still think it would have been better to use a sample from a  more neutral market rather than the preselected mailing list that we used.  I had been concerned  about the fallout from leading customers to a checkout page only to tell them that they couldn’t  actually complete the purchase, but I was pleasantly surprised that they were not upset and 100% of  them elected to be informed when it was available.

I really liked using this tool and I’m looking forward to doing more work with it.  The single biggest  takeaway for me is that it is virtually impossible to predict customer behaviour but extremely easy to  record it when it is happening.  This makes a Learning Launch an excellent tool for design.

