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When we think of brand experiences that stand out, personalized recommendations are paramount. 91 percent of consumers say they’re more likely to shop with brands that provide offers and recommendations that are relevant to them. What’s more, they’re willing to share information for a more personalized experience versus an experience that is not personalized. But as consumer journeys have grown more complex, the number of “if-thens” that had to be accounted for multiplied, and the scale of recommendations became unwieldy, defeating the original promise of addressing a single person with the best recommendation.

To finesse this tension, marketers began creating AI models called next best action models, which use customer profile data and previous behavior to create classifications and, ultimately, select a recommendation to serve to the customer. These models came closer to solving the problem but were limited by the extent that they could:

  1. Understand customer intent, or the causal reason why a customer is interacting with a brand
  2. Adjust recommendations based on aggregates and/or identify outliers and anomalies
  3. Integrate with the systems of action needed to execute in the middle of a consumer’s journey

When we put these existing technical limitations in the context of our evolving privacy landscape, these approaches become more problematic. For example, even the most robust Next Best Action models are click-based, relying on third-party unique identifiers, like cookies. Google has announced that these methods will be blocked by 2023. Brands will have to get equivalent contextual information from another source, threatening traditional next best action models with obsolescence.

With shifting paradigms around privacy and consent, marketers need to think about personalization differently. Marketers need to consider how they receive data, act on it, respect consent, gain opt-in, and always try to understand the user’s intent to guide the recommendation. Historically, the key pillars of personalization have been:

  1. Triggers: What interactions or events will prompt personalized engagements?
  2. Content: What assets do you need to deliver personalization?
  3. Channels: Which channels will carry the personalized engagement?
  4. Data: What data do you need to understand your consumers to decide the above?

Enter conversational AI technology

Conversational AI is currently the best answer to the first-party data imperative, because the best way to understand what customers want or need without resorting to surveillance tactics is to simply ask them. Through web, app, social, and mobile messaging channels, conversational AI gives brands the ability to engage customers in two-way interactions and provides an opportunity to both personalize an experience in the moment, and, to succinctly and clearly ask for consent. AI-powered conversations are:

  • Consensual: By nature, conversations are consensual. They are both two-way and “give-and-take.” Customers willingly enter and can willingly end conversations at any point. Natural language understanding empowers brands to build automation that clearly defines what data they are looking for, how they plan to use it, and for how long they would like to use it. This makes it easier for customers to make informed choices and for companies to understand those choices explicitly.
  • Convenient: With AI-powered messaging, brands are meeting customers in their conversational channel of choice — Apple Business Chat, WhatsApp, Facebook Messenger, SMS, web or others (including Discord, Telegram). Because it is asynchronous by nature, whatever the channel, communication happens on the customer’s time and terms — not the brand’s.
  • Considerate: A powerful and continuous stream of first-party intent data gives brands the power to tune and refine user journeys. Users have more control and brands can tailor experiences directly to customers’ needs (and create experiences worth sharing data for in the first place).
  • Continuous: Every single touchpoint in the customer journey can take place through a single conversation thread, if needed. From discovery, to purchase, to care and service, customers can refer back to a single touchpoint instead of many. Their past conversations can also be made available for as long as they want them to be.

When marketers embrace conversational AI and messaging as a central component of their customer engagement and personalization strategies, first-party conversational data will surpass first-party clicks for these reasons.

LivePerson proprietary data shows that conversational AI has a positive impact on conversion rates, customer satisfaction, and customer lifetime value. When done right, personalization brings value to consumers’ lives, driving brand loyalty and increasing revenue. When done poorly, it can have the opposite effect — and the ramifications of poor personalization experiences are only going to get more extreme in the ever-evolving data privacy and security landscape. Third-party identifiers are on their way out, and the GDPR era, “We use cookies, is that ok?” pop-up messages aren’t going to cut it for long. The good news is that most people are still willing to share their data if it helps to create an experience that they believe is valuable to them. As consumers gain more and more control of their personal data and more understanding of how it can be used, brands will have to work double-time to earn and keep first-party data.

Next Best Conversation

LivePerson is proud of our partnership with Adobe and our joint solution, Next Best Conversation™, that gives brands the ability to gracefully combine user intent and user consent, resulting in powerful experiences and high fidelity data that can be used to remake recommendation models without the privacy dilemma. Here’s a glimpse at what two Next Best Conversation models look like in action:

Growth Model:

  • Triggers contextual messages that offer support across a shopping journey
  • Help remove friction for users viewing high-consideration products
  • Drive increased conversion rates
  • Offer support when a customer may be confused about pricing or charges, reducing abandonment rates.

Service Model:

  • Provide proactive support based on when a customer had an order fulfilled
  • Check in to make sure an order was satisfactory, opening up a conversation opportunity to get ahead of and address any customer service needs
  • Increase CSAT by as much as 20 percent by lowering resolution time

Conversational AI is the modern solution for personalization strategies fit for the cookieless world, and beyond. Conversations consensually capture first-party intent data and allow brands to connect with consumers on the individual level and on the individual’s terms. Digital transformation means going direct-to-consumer, reducing wasteful costs, driving growth with digital goods and services, and meeting consumers on their terms.

LivePerson and Adobe have a strategic partnership that enables personalization across digital and conversational experiences, at scale. LivePerson’s Next Best Conversation powered by the Conversational Cloud, integrated with Adobe’s Experience Cloud and Real-time CDP enhances the customer’s journey and enables brands to delight customers by delivering highly-contextualized messages, recommendations, and offers that are unique to their explicit needs on a consumers’ preferred messaging channel. The added layer of LivePerson’s best-in-class NLU, built off of more than 20 years of customer conversation data, allows a brand to apply this comprehensive understanding of customer intent to its personalization strategy, creating a two-way connection between the customer and the brand, that strengthens over time.

Contributing Author: Max Kirby is Product Director, Identity & Privacy at LivePerson. Previously, he led the Customer Data Platform and Cloud Computing Practices at Publicis. Kirby has been a privacy advocate, digital identity expert and award-winning speaker for 15 years.



ahmedaljanahy Creative Designer @al.janahy Founder of @inkhost I hope to stay passionate in what I doing

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