At PegaWorld 18, Pegasystems has announced a new product called Self-Optimizing Campaigns. The Pega AI will ingest as much data as possible about the audience and the campaign. It will use that data to ensure that a campaign is personalised to the extent where it becomes a one-to-one engagement.
Pegasystems claims that this will simplify existing campaign creation. Reducing complexity will lead to lower costs. It will also ensure that marketing is likely to get a better response from the audience.
Tom Libretto, CMO, Pegasystems said: “Over the years, many in martech have prophesized the death of inefficient and ineffective marketing segmentation. But in reality, most still struggle to transition from these long-entrenched strategies.
“With the launch of Self-Optimizing Campaigns, we are accelerating the path to one-to-one marketing with more accessible AI campaign power that does all the heavy lifting. We’re making every offer smarter to increase conversations, lower time to revenue, and drive higher profits.”
How will Self-Optimising campaigns work?
Large campaigns are already created as multi-wave activities. With self-optimising campaigns, the gap between waves will be used by the Pega AI to evaluate the results and tune the next wave. In a traditional campaign setting this would have been complex and the tuning would have been limited. By allowing the Pega AI to learn from and adapt the campaign, the gap between waves will be vastly reduced.
One of the benefits of reducing the gap between waves is to improve audience retention and response rates. Another is the way that the audience is selected. The Pega AI will select the most relevant audience from the information on individuals and their likely response triggers. It will then create a mix of offers, actions, and treatments to achieve the campaign goals.
The announcement highlights three key improvements that self-optimising campaigns will deliver:
- Automated audience selection: Marketers spend an excessive percentage of their time researching and extracting customer segments for their campaigns, generally with subpar results. With Self-Optimizing Campaigns, marketers simply input the desired size of their audience. Pega AI automatically finds the most relevant targets and fine tunes its selections as the campaign progresses.
- Multi-offer, multi-treatment scope: Most campaigns are limited to a small number of offers and a limited number of A/B-oriented tests. With Pega’s AI, marketers can introduce a nearly unlimited number of offers, treatments, and test scenarios in a single campaign. The system automates away most of the complexity, using each individual’s unique needs and preferences to align the campaign message with the target’s current context.
- In-flight campaign optimization and testing: Marketers don’t need a PhD to take advantage of Pega’s easily accessible AI power. They simply set their campaign goals, such as acquisition volume, churn reduction, or cross-sell response rates. Pega AI does the rest, using adaptive analytics to continually balance the campaign mix. Automated testing runs continually in the background, learning which combinations work best for each customer.
What about privacy legislation and opt-in?
This is a more complicated problem for marketing organisations. The introduction of the European General Data Protection Regulation (GDPR) is already creating problems for marketing organisations. Many US websites have blocked European visitors as they don’t know how to manage opt-outs and data sharing with marketing partners.
European sites are already feeling the pinch. Rather than a simple opt-in to receive marketing statement, they now need to list all companies who may access data. Customers have the right to choose which, if any, of those partners will be allowed access to their data. It means that there is likely to be a major hole in marketing data.
This is where use of the Pega AI will also need to be carefully considered. Its power is in being able to ingest large amounts of data from multiple sources and create connections between data elements. Those connections will lead to customers receiving offers and other marketing materials.
What will be important is how well the AI can demonstrate where it got the data from. It will need to have the right safeguards to ensure that all source data is opt-in only. In addition, where it mixes anonymous data to refine a campaign, there will need to be safeguards to ensure that it does de-anonymise the data. If it does, then organisations will have to treat this as personal data.
What does this mean
The growth of AI systems in marketing has begun. There are a number of companies who see AI as being the solution to a shortage of data scientists. They are also keen to take advantage of its ability to refine data and create more effective marketing.
With Self-Optimised Campaigns, Pegasystems has provided them with a tool that many will want. What is not clear is how much data cleansing and training customers will have to do. Bad data into the AI will lead to ineffective and disappointing campaigns.