Ecommerce & Attribution Case Study
An eCommerce coffee company was experiencing stagnant sales (at approximately $20M) and increased customer acquisition costs due to rising competition.
PIN provided support in the following areas:
Target Audience Analysis
Subscribers vs Non-Subscribers
We began by focusing on new, cold audience identification and activation through novel attributes producing attitudes, motivations, and affinities in addition to standard demographics. We accomplished this through data enrichment and audience DNA Reporting, in addition to Principal Component Analysis (PCA), and this resulted in audiences featuring Crossfitters, DIYers, Hunters, Snow Sport Enthusiasts, and more.
Home Owning American Providers
- 31-35 year old male of American descent
- Married with children
- Owns a single family home
- Lives in a large metropolitan area
- Has some college
- Blue collar Republican earning $50K-$75K
- More likely to own a used truck than new mid range vehicle
- Interested in Health & Fitness program
- High interest in DIY home renovation and invests in home improvement
- Unlikely to be a deal seeker or recreational shopper
- More likely to stream TV than have cable subscription
- More likely to utilize digital newspaper than traditional newspaper
Multi-Channel Attribution Modeling
The client relied heavily on last-touch reporting models through disparate sources. In doing so, they experienced jaded results and “double counting” as the big tech companies aimed to take credit for producing a desired action. In building first-touch, last-touch, and multi-touch models, we were able to illuminate the divergence occurring throughout a given conversion pathway and better allocate marketing dollars to create efficiencies and decrease customer acquisition costs.
After identifying new audience segments and determining the ideal marketing channel mix, we built campaigns and messaging designed to drive net new customers who were previously neglected with the products that they were most likely to purchase. This resulted in substantial increases in sales from new customers and growth in market share.
Current Customer Nurture Strategy
The client manually deployed email campaigns multiple times monthly and needed a strong return. PIN monitored user journeys and failed conversion pathways to identify triggers on the site that could be tied to an automated email and SMS outreach. This included new campaign logic and overlays of machine learning. This process was designed to engage our recipients and present them with product offerings when they had the highest propensity to engage. Some examples can be seen below:
- Second Purchase Series
- Product Replenishment
- Predictive Winback
- Gift Purchase Reminder
- First Purchase
- Emerging Best Customer
- Best Customer (Frequency of 5) – Social Push
The client grew their Annual Gross Revenue to $100M after 24 months on the PIN Platform, up from $20M. They were also to increase their Return on Ad Spend, which was increased by 4.5x from 1.5x before working with PIN. And their Automated Nurture Program was attributed to 10% of Revenues, previously non-existent before PIN.