John McMahon

Our product strategies led to doubling the company's revenue focused on addressing critical business opportunities and key shopper needs identified through market research, user research, and product analytics.

Note: Giving Assistant is a three-sided eCommerce marketplace that makes it easy for shoppers to save at their favorite brands and give some or all of these savings to a nonprofit of their choice.

Like many product ideas, this opportunity was surfaced through product analytics. Our data analysis involved running full-funnel analyses across key user segments. We looked at dropoffs and weak conversion points. We also dove into lifetime value, acquisition costs, and retention numbers for these same user segments.

Once we had a solid understanding of the data, we wanted to confirm assumptions and hypotheses by running user interviews. This approach allowed us to understand the why (user motivations) behind the what (user actions). It provided the opportunity to iterate on prototypes with real users. We also took inspiration from our competitors.

This baseline guided the scope of the MVP offering and delivered designs for mobile and desktop and an initial list of experiments. From here, the project took a normal agile development approach. Once launched, we ran weekly experiments for several months.

In the end, this data-informed product opportunity lifted the YoY earned cashback rate (shopper activation) by 21%.

Note: Giving Assistant is a three-sided eCommerce marketplace that makes it easy for shoppers to save at their favorite brands and give some or all of these savings to a nonprofit of their choice.

A3D allowed digital marketers to define audiences from psychographics, such as people who are passionate about a brand and show high purchase intent for one of its products, and surface messaging and images known to move and resonate with them.

To get the offering right, we studied our competitors, looked at industry trends, and ran customer interviews with first prospects and then real customers in our new customer charter program. The purpose of this program was to get an initial investment from customers so that they would be engaged throughout the product's development. It led to a strong understanding of the needs and workflow of digital marketers. With this baseline, we could start testing potential product opportunities and our biggest risks.

One of these risks was the amount of required data. Since one audience could consume millions of tweets, we knew we could easily exceed our monthly allotment with Twitter. It was a challenging data problem that resulted in leveraging smaller, sampled audiences.

Another risk was getting the user experience right. To succeed, we ran ad campaigns to figure out the offering and interactions. We polished our design through iterations of a prototype with customers.