Organizations today are drowning in data, but starved for insights. This makes it tough to get a handle on how to deliver the best experience for each customer. Adding to the challenge is that data often exists in silos within the organization—some owned by IT and data science teams, some by sales and more with customer service.
As a result, marketers are finding it practically impossible to deliver on the personalization that today's customers are demanding from their favorite brands. This is especially true when they try to use traditional offer creation and deployment tools, which are created for segments, not individuals.
For marketers facing these problems, artificial intelligence (AI) and machine learning (ML) are game changers. It’s true AI and ML are all the buzz these days, with virtually every martech platform claiming to use these technologies to support personalization. But in reality, many of these software companies do not truly capitalize on the power of AI and ML.
AI is generally described as applying human intelligence to machines. When the machine completes tasks based on a set of problem-solving rules or algorithms, this is “intelligent” behavior. AI is a broad concept that includes “good old-fashioned AI” to futuristic technologies, like deep learning.
ML is a subset of and a technique for realizing AI. ML empowers computers to learn. Instead of teaching the machine to complete a task by programming a specific set of instructions, ML uses algorithms to ingest massive amounts of data. Then it learns how to perform the task based on the insights it continuously gathers.
We understand that personalization is the #1 challenge for marketers, and doing it at scale can be next to impossible if they only have access to traditional technologies and techniques.
Our solution takes a unique approach, applying ML to help our customers automatically identify relationships between disparate data, breaking down the data silos that have prevented personalization in the past. As more data is gathered with every customer interaction, the ML algorithms get smarter, enabling brands to quickly test and analyze alternatives, then fine-tune offers to deliver the most impactful customer journey to each individual.
Because it’s automated and doesn't have to be explicitly programmed, Formation's ML-enabled solution can help bridge the gap between your data science team and marketing, giving marketers the tools to quickly and effectively develop offers they send to customers at scale. Using conventional tools, it could take three to five months for large brands to segment and send offers to customers. And only about a thousand offer variations could be created for just 10 to 30 segments at most.
By applying ML, not only does Formation speed up the process, it also enables it to be done in less than 10 days. We also help customers optimize offers, so they are producing millions of offer variations and achieving true 1:1 personalization. Yet another differentiator: We support weekly measurement of marketing efficiency, rather than only being able to do this on a quarterly basis, as most companies currently do.
Our customer Starbucks is a good example of the power of ML. Using Formation, they were able to reduce the time to develop and launch offers by 10x and increase offer variations by 100,000x, to truly reach and engage rewards members on an individual level.
The beauty of ML is that the more data you have, the better the results. So over time, using Formation, you can continue to learn from customer interactions, and reach the pinnacle of marketing: true 1:1 personalization.
Interested in learning how you can leverage AI and ML to deliver personalized offers? Contact us for a demo today.