Without actionable data, customer experience strategies are doomed. Lisa Loftis, Director of Customer Intelligence Solutions at SAS, discussed some interesting CX findings from Futurum Research in her presentation at our MarTech conference.
“One of their most important findings is that the future of CX lies in the analytics of real-time data collection and the ability to adjust these activities so that you can proactively meet and exceed requirements. customers,” she said.
She added, “In our philosophy, data doesn’t change the organization, decisions do.”
Marketers have a responsibility to add more data to their decision-making processes, especially given the technologies available. Marketing automation platforms have made decision-making more efficient by streamlining tasks that were previously time-consuming for marketers.
“Decision automation is not a new priority for marketers and CX managers,” she said. “The problem is that the pandemic-induced digital behaviors we’ve been talking about have heightened the importance of decision automation in CX.”
Here are a few reasons why successful CX strategies require data-driven decision making.
Data adds customer context
Data pulled from analytics and CRM systems can provide marketers with much-needed context to make better campaign decisions. Plus, these tools can create the foundation brands need to automate these choices in the future.
“You can start to understand how relevant the business is to the customer,” Loftis said. “Do they have products? Do you have any products they want or need and what do they think of their past interactions with you? This information almost exclusively falls under the CRM category and can be used to understand things like segment behavior and offer personalization. »
She added, “We can begin to understand what motivates an individual and what their influence value may be. The data that makes up personal context comes from a mix of third-party purchased information and social media activity.
Automation determines the next best actions
Loftis provided an anonymous case study of a large bank that used automated decision making, helping to illustrate the benefits of automation. She described how the campaign generated significant benefits for this bank, generating 6 million leads per year and 80,000 to 100,000 new accounts per year with a marketing ROI of over 100% in the first few years.
She also described the process by which successful marketing teams work with these technologies: “Marketing groups generate individual targeted prospect lists that are submitted to a central decision engine. The engine uses a combination of predictive and machine learning analytics, business rules and predetermined constraints to develop a list of potential deals for each customer. »
She added, “So when the customer…visits an included channel, the channel contacts the decision engine to get a list of possible offers.”
Marketers would be wise to check out the automation system they’ve chosen, making sure that its decision-making process aligns with the organization’s goals. When properly deployed, these technologies can optimize customer offers in real time to deliver the best possible CX.
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Continuous data powers decision-making
Many organizations have turned to data streaming, a solution designed to solve data pipeline problems, recognizing its value in decision-making.
“Streaming data isn’t new, but the way we process it has changed significantly over the past few years,” Loftis said. “In effect, it was a scaled-down version of the data warehouse, another data silo, and it existed for a reason: to store data.”
“The problem was that there was almost always a lag in the process,” she added.
Data streaming can help marketers capture and aggregate large amounts of customer data, which can be used to power automated marketing processes. All of this is also done in real time to ensure smooth customer experiences.
“To meet customer expectations, streaming data must be analyzed and processed as soon as it arrives in the stream, not hours later,” Loftis said. “Data and analysis results can still be stored for later use if the nature of the actions does not require real-time delivery. But today’s digital engagement models mean we need to apply analytics to data as it moves through the stream. »
She added, “The goal of a true streaming data platform is to apply high-end analytics directly to data.”
Overview: Marketing Automation
For today’s marketers, automation platforms are often at the center of the marketing stack. These aren’t shiny new technologies, but rather reliable mainstays marketers can count on to help them stand out in a crowded inbox and on the web amid a deluge of content.
HubSpot noted late last year that marketing email volume was up 52% from pre-COVID levels. And, thankfully, response rates also increased between 10% and 20% from their baseline.
To help marketers gain attention, marketing automation vendors have shifted from relying on static email campaigns to offering dynamic content deployment for emails, landing pages, and more. destination, mobiles and social networks. They’ve also incorporated features that rely on machine learning and artificial intelligence for functions like lead scoring, in addition to investing in user interface and scalability.
The growing popularity of account-based marketing has also influenced vendor roadmaps, as marketers seek to serve the buying group holistically, addressing all of its members and their different priorities. And, ideally, these tools allow marketers to send buyer insights through their tight integrations with CRMs, giving the sales team a head start when it comes to closing the deal. . Learn more here.