Twenty years ago, the Internet was just starting to boom and artificial intelligence (AI) felt like a pipe dream. Back then, organizations built response models the old-fashioned way—with analysts, raw data and computer programming.
Much has changed in the last twenty years—but one thing remains the same: response models enhance targeting, timing and dramatically improve marketing ROI.
Artificial Intelligence Statistics You Need to Know
Technology continues to advance and change the way we gather information for the better. In this “digital age”, business intelligence (BI), artificial intelligence, data mining and predictive modeling are dominating the tech scene. And it’s not just the Amazons, Googles and Facebooks of the world that are taking advantage. Many CEOs and executives are realizing that they have much to gain from these vital, data-gathering tools.
The statistics speak for themselves:
– 80% of business and tech leaders say AI already boosts productivity (Source: Narrative Science)
– 72% of business leaders say AI can enable humans to concentrate on more meaningful work (Source: PWC)
– Companies using analytics, such as BI, are five times more likely to make faster decisions (Source: Forbes)
– AI will boost profitability by 38% and generate $14 trillion of additional revenue by 2035 (Source: Accenture)
Using AI and BI with Direct Mail Marketing
Despite the growing transition to data-collecting technology, there’s a concern that companies—some of which are very large and have sophisticated marketing teams—aren’t taking advantage of AI, BI, data mining and predictive modeling in a way that improves their direct marketing efforts.
Even though businesses continue to employ more data scientists and collect more data, somewhere they forgot that one of the best places to act on this data is in direct mail. In fact, Hallmark, the long-time leader of greeting cards, helps businesses utilize direct mail marketing to boost their bottom dollar.
– In 2018, the marketing ROI of direct mail increased by 12 percentage points and exceeded the ROI of online display advertising (Source: ANA/DMA Response Rate Report)
– Direct mail produces the highest response rate of any medium, and direct mail and social media are tied as the second most used medium by marketers (Source: ANA/DMA Response Rate Report)
– 76% of consumers trust direct mail when they want to make a purchase decision. Actually, consumers trust traditional advertising channels more than digital channels when making a purchase (Source: MarketingSherpa)
– 75% of households usually read or scan direct mail advertising materials (Source: The Household Diary Study 2016, USPS®, Table A8-15)
Clearly, there is value in using direct mail to engage customers and foster relationships. Hallmark routinely demonstrates that value through successful collaborations with companies all over the country. For example, every dollar spent on Hallmark cards by a clothing retailer generated an average of $38.00.
Personalization, Prediction and Performance: Why They Matter
Here at Hallmark Business Connections, we bucket the future benefits of AI, BI and predictive models very simply into 3 Ps:
Improving personalization extends far beyond using a person’s name. Think of personalization from the recipient’s point of view with this question, “How can I improve the relevancy of this communication?” Data attributes used individually or combined often lead us to change the words and images we use in our Hallmark greeting cards for companies.
Great personalization also excludes irrelevant information. As marketers, we are naturally wired to want to talk about everything a consumer could buy from us. The trick is to talk only about the most important product to that individual consumer. Sometimes it’s what you don’t say that matters most.
Data scientists will point us to lots of useful information, but when asked a question, such as, “Can you tell me what data inputs are driving the predictive model?”, they may get frustrated. It’s important to remember that it is a unique combination of data elements that typically drive a model. No matter if a model is built from scratch, using AI or other logic, it’s impossible to point to a single factor (like age, location or past purchase history) and say that it’s predicting the outcome. That is what makes AI and predictive models different from targeting by segment, demographic or psychographics.
Predictive models can inform us as to when someone needs a marketing touchpoint, when they are likely to leave or when they are positioned to buy additional products. More advanced models can help predict what offer, mail format or communication stream will drive the best performance.
Incorporating AI, BI and predictive models into your direct marketing can make the difference between meeting your marketing goals and falling short. Applying data intelligence improves personalization, relevancy, timing, offer selection and more—just about every aspect of a direct mail program. One advantage of using AI and predictive models is not only that it improves who you mail to, but it also helps avoid mailing to those who are not likely to respond. NOT mailing to the wrong people has a dramatic impact on profitability.
Important Lessons for the Marketer Who is Unfamiliar with Direct Mail
If direct mail isn’t necessarily in your wheelhouse, or if you’re a marketer who primarily focuses on digital tactics and strategies, take a look at our three pieces of advice below:
1. Collaboration is critical. A data scientist will not know the business like the marketing team. Learn from each other.
2. Use data legally, ethically and in the best interest of the customer. Improve their experience and you’ll improve your marketing ROI.
3. Give it time. Iterate on the model or allow time for machine learning to take place.
Case Study: Hallmark Greeting Cards as a Targeted Direct Mail Tactic
When you effectively use your collected data to drive your direct marketing campaign with assistance from Hallmark Business Connections, great things can happen. If you asked companies who’ve sent Hallmark greeting cards to their customers, they would tell you that their message was opened, read, understood and acted upon better than other format.
Take this case study, for example. A specialty retailer wanted to beat its 4% response rate and drive a higher ROI. Hallmark customized a greeting card that fit the brand and included a message of appreciation along with an insert showcasing an offer. Customers also received coordinated emails reminding them of the offer. Response rates rocketed to 22% in online and in-store sales.