Codeless AI leverages agencies’ strengths to drive hyper-personalization of direct mail. The results are significant uplifts in campaign effectiveness with large reductions in costs.
The Business Challenge: Achieve marketing program objectives while reducing costs.
In case you think those glory days of direct mail are over, consider this: Direct mail is a nearly $50 billon industry in the US, with advertisers achieving 5% response rates and 1,300% ROI. Volume is at all-time highs.
Success in direct mail depends on knowing your target and deploying the right message and creative for the right individual. Great agencies and marketers are the ones that combine analytics and creative to incite action. Even when analysts, strategists, and creative teams are in the “best” category, controlling costs to improve return on program investment is the number one challenge agencies face. Firms that employ artificial intelligence to get an edge in that quest are now the highest performers.
Hyper-personalization—sending the strongest messages, in the best formats, at the correct times, to the right people—pays big dividends. It makes sense. If you know what types of marketing materials will resonate with a target, you can tailor your package to match. If you know the likelihood of response by recipient, you can optimize spend. Most of all, if you know which messages resonate from brain to wallet for each recipient, you gain repeat revenue from target audiences.
The Transformation: AI power without data science teams
Squark helps agencies hyper-personalize client campaigns. Understanding target audience behaviors are essential to creating effective campaigns, but mere insights are not sufficient. Practical implementation of hyper-personalization means predicting exactly what message and package will prompt an individual to respond. The essence of hyper-personalization is making each person a segment of one. That’s what increases response rates, and what propels cost reductions in customized printing, mail shop services, and bulk postage. Knowing the who, what, and more important than ever.
The Squark process is simple. Data sets containing known outcomes from past mailings are uploaded directly to Squark with a few clicks. That’s the training data. A production file is then uploaded. That’s the set of records on which to predict. Squark then builds and compares scores of models. The most accurate algorithm is then used to produce row-by-row predictions on the production data and they are returned to the agency.
Machine learning detects patterns in existing data and predicts how never-before-seen recipients will behave. In addition, Squark ranks factors in order of their predictive importance, so that agencies automatically discover which features are critical to a campaign’s success. Personas revealed from predictions make it easier for creative teams to produce appropriate messages and imagery that are then incorporated into the fundraising strategy.
Squark is direct, clear, fast, and intuitive to use. Squark cuts modeling time down from the weeks it could take with custom programming to just hours. Dozens of iterations and refinements can happen in a fraction of the customary time. This is the essence of how Squark moves past insights to drive actions. Actionable output feeds actual campaigns.
The Results: More net revenue; Better engagement.
Squark drives immediate uplift in direct marketing campaign response through better targeting—engaging the right prospects with the right messages. Production and mailing costs drop significantly by avoiding people who discard pieces without consideration. That is the simple formula for monumental increases in return for large campaigns.