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Case Study

Ford: Driving CX improvements with next-best-action

  • Self-optimized campaigns, driven by adaptive models
  • Improved timeliness & relevance of customer conversations
  • Increased marketing velocity

"We’re working really hard to improve the customer experience. To do it, we've got to make every communication relevant. That’s where Pega comes in. We turn to Pega to make those few opportunities we get with a customer really count."

The Business Issue

The automotive industry is shifting business models; from simply building the best machines to creating the best customer experiences.

But figuring out who is in market and for what, can be challenging – especially when there are long periods of time between interactions. When engagements may be few and far between, every single one is critical. To take advantage of these tiny windows of opportunity, the one thing that matters most is relevance.

For Ford, traditional marketing campaigns no longer cut it. Velocity was simply too slow. With long test and learn cycles and unactionable results, Ford needed a better way to keep pace with their consumers.

The Solution

With Pega’s Self-Optimizing Campaigns, Ford launched their “Communications Optimization” revolution. Backed by adaptive models, they transformed customer engagement into a two-stage process; explore and exploit.

During the initial exploration phase, messages are sent to a randomly-selected control group. Immediately after being sent, Pega begins collecting the results: Did they open? Click-through? Did they go to the web? What did they do there? How engaged were they? The collected data feeds the model and it begins to learn which messages are most effective for which customers.

Those decisions power phase two, exploit – a series of multi-wave campaigns in which Pega moves customers in and out of next-best-action audiences in real-time.

The Results

In just three weeks of Ford’s “FordPass Mobile App” campaign, they engaged over 300,000 customers and saw a 26% increase in conversion.

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Tags

Industry: Manufatura
Área do produto: Customer Decision Hub
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