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Autonomous Engagement

Autonomous engagement: The holy grail of achieving personalized customer experiences

Kyle Munderville,
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Every day, consumers embark on a multitude of journeys beyond strict buyers’ journeys just by living their lives. They’re not just shopping, but also tending to their loved ones, purchasing homes, bonding with friends, consuming content, researching, organizing, driving, cooking, and simply existing. Amidst all of this, they are generating a staggering amount of data – billions of data signals each day. How can organizations keep up with them and meet the distinct needs of each unique individual? As humans, it’s simply not possible. In today’s era of hyper-growth, businesses are unable to hire, train, and retain enough employees to scale and meet the ever-evolving needs of millions of customers as they engage across every single touchpoint a brand has. But artificial intelligence can. And it is empowering businesses to engage autonomously to maximize sales and revenue, while balancing the critical relationships that keep brands top of mind so that they can grow at the rate that stakeholders require.

Autonomous engagement defined

How does it work? Autonomous engagement is when artificial intelligence (AI) is trusted to interact independently with customers across the enterprise and learn from those interactions to the point where AI is not just making tactical engagement decisions but is actually recommending and shaping a company’s strategies. That includes:

  • Orchestrating customer interactions independently across all channels; mobile, email, web, direct mail, chat, IVR, retail or branch, paid media, search, SMS, and beyond. 
  • Automatically self-learning from cross-channel engagement results to improve relevance and personalize as a customer’s context changes.
  • Continuously projecting and comparing opportunity costs to prioritize customer lifetime value.
  • Maintaining the balance of human relationships versus business performance.

All in service of delivering better customer experiences, better employee experiences, and better business outcomes.

The autonomous engagement continuum

Achieving autonomous customer engagement is a journey. Though it is enabled by AI, it is about much more than that. At its core, autonomous engagement is about organizational change, trust, and transparency. This journey is made up of four stages, with organizations across the enterprise enabled at varying levels.

  • Human stage is the foundational stage that relies on human labor as the primary driver of content, creative, tactics, and strategy. The manual processes that occur here usually take weeks to complete and involve building a business case, getting proper approvals, and executing against a strategy.
  • Automated stage is where organizations enable greater scale and efficiency by operationalizing data and automating human-engineered initiatives. Marketing automation allows brands to create business rules and triggers to engage with segments of consumers that share attributes. At this stage, communications have more meaning and relevance than email blasts to an entire database of contacts.
  • Self-learning stage is when machine learning becomes the driving force, working to predict what the customer wants and needs. To provide a great customer experience, the AI at this stage must be capable of constantly learning, adapting, and converting data and signals into insights.
  • Self-optimizing stage is about creating a centralized, single executive control center. AI takes a more strategic role, constantly simulating outcomes to optimize strategy, with guardrails to safeguard stakeholders. In this stage, AI helps to balance strategic trade-offs and opportunity costs.

How to achieve self-optimization

As the leader in real-time decisioning, Pega is perfectly suited to help brands move to the self-optimizing end state. Real-time decisioning makes powerful and accurate decisions very quickly, calculating next best actions. Those actions help executives better understand their customers and gain insights into what exactly to sell and to whom, as well as how to retain a customer or when it might be time to intervene and help them solve a problem. By doing this, brands are able to increase response rates and conversion rates, and drive a massive amount of new customer value every year – generally hundreds of millions of dollars. All while building stronger customer engagement.

But it doesn’t stop there. The requirements to keep customers happy today are constantly shifting. To remain relevant, organizations have to maintain hundreds of evergreen campaigns at the same time. More than just a catalog of offers, brands need to have retention, nurture, and service communications – the things that customers want that provide a great experience. This is how customers stay loyal. All of those potential communications would take weeks or months to manually create and action against. And how would you ensure you’re operating quickly – and strategically – at scale, without losing your customer? Enter self-optimization.

Imagine what can be achieved when your organization reaches the self-optimizing stage. You already know what works and what doesn’t. You have the automation and self-learning in place. And now you can take that to the next level with optimization. With one quick motion, brands can adjust entire campaigns based on shifting business needs. Organizations can test different buyer personas, create audience simulations, compare different actions, and ensure those actions remain ethical. And that can be done countless times, at scale. At the self-optimizing end state, executives and business leaders are able to make big picture decisions to achieve specific, and varying, business outcomes – all with the help of a centralized, always-on brain. Autonomous engagement is about much more than just technology or AI. It’s about building trust with your customers and operating in a way they respect.

Start the transition to autonomous engagement now

Brands should waste no time beginning their autonomous engagement journey. One-to-one personalized marketing is already achievable through real-time AI and can lead to increased engagement, response rates, and customer satisfaction. To learn more about achieving truly personalized customer experiences, download our whitepaper today: Crossing the chasm: From traditional marketing to one-to-one customer engagement.


Thema: Autonomous Enterprise Thema: Kundeninteraktionen

Über die Verfasserin

Kyle Munderville is a product marketing manager at Pega who enjoys using storytelling to bring attention to the transformational power of technology and highlight the unique ways businesses can streamline processes to solve specific problems.

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