Raviteja Dodda (Ravi) is the cofounder and CEO of MoEngage, an insights-led customer engagement platform.
In an era of do-more-with-less, consumer brands face mounting pressures to drive growth with limited resources. While customer engagement is the clearest path to growth, ever-changing consumer expectations make it extremely difficult to keep pace. More data, channels and demands compound these challenges.
Faced with these mounting pressures, brands have started to turn their attention to artificial intelligence (AI) as a solution. AI-driven strategies promise deeper insights and better connections with customers in more meaningful ways. However, in rushing to adopt AI, brand leaders now face “AI overload”—an endless stream of tools causing dilemmas in identifying the most impactful solutions.
As the founder of an AI-powered customer engagement platform, it’s been exciting to be at the forefront of AI adoption to help brands drive growth. While I recognize things are quickly changing, we’ve already uncovered some valuable lessons for success. With that in mind, here are some ways brand marketers can avoid AI overload and strategically leverage this technology to drive deeper customer engagement and meet growth goals.
Applications Of AI For Enhanced Engagement
Here are four ways marketers can apply AI to gain a deeper understanding of the customer experience across multiple engagement channels:
1. Comprehensive Data Analysis
The amount of customer data available to brands is exploding. But making sense of web analytics, in-app behaviors, purchases and preferences overwhelms teams. AI offers the next evolutionary step in customer data analysis with the ability to digest boundless data sets no human ever could. It analyzes information, runs endless amounts of real-time tests and predicts outcomes—all while continuously optimizing in the background. This frees teams from manual analysis to focus on creativity and customer connections.
2. Contextual Personalization
Think of your best customer experience—how a brand seemed to truly understand and cater to you. Personalized engagement is the magic behind this experience. It’s impactful, and it matters. Not just for improved customer experiences but for better business growth. Companies that grow faster drive 40% more of their revenue from personalization, according to a report by McKinsey & Company. But tailoring engagement across channels and customers is enormously difficult. AI systems can take individual customer insights and orchestrate relevant cross-channel personalization at scale. The result is a tailored, proactive experience for every customer.
3. Process Automation
There is no doubt AI automation has tremendous potential to greatly improve efficiency. In fact, Gartner predicts brands leveraging AI for multichannel engagement will elevate operational efficiency by 25% by 2025—a welcome relief for brands that are already stretched thin. It excels at high-volume repetitive tasks like data cleansing, report combining and campaign tracking that previously bogged teams down. When leaders thoughtfully apply AI automation to their internal processes, they can focus their human talent on high-impact initiatives.
4. Predicting Customer Needs
AI’s predictive power enables brands to get ahead of customer needs through analytics of behaviors, interactions and preferences. It identifies subtle shifts that human analysis alone could miss, such as churn risk, service issues, up-sell opportunities or optimal times for engagement. These insights allow brands to engage contextually at just the right moments. Identifying customer needs through prediction is just the first step, though. In the next section, we’ll cover how to leverage predictive intelligence to improve customer experiences and engagement.
AI’s Predictive Capabilities
AI’s predictive capabilities empower brands to foresee trends, behaviors and outcomes, reshaping industries across the board. For instance, e-commerce giants leverage AI-driven product recommendations to enhance user experiences, increasing customer engagement and sales. Financial institutions employ predictive analytics to detect fraud proactively, safeguarding assets and consumer trust. Media companies fine-tune content recommendations through AI, boosting viewer satisfaction and retention.
Trust-Based Considerations For AI
While AI offers immense potential, it also brings significant risks if ethics and consumer privacy are neglected. To maintain ethical integrity, brands must establish clear guidelines for unbiased, transparent and privacy-focused use of customer data. Rigorous testing is essential to eliminate bias in predictive algorithms. Ethical oversight should be an ongoing process, adapting to emerging issues as AI models evolve.
Responsibility for ethical AI adoption should be shared across an organization, involving data, analytics, operations and leadership. Customers should be empowered to control their data through transparent policies and opt-in consent.
Every piece of collected data must serve a clear business purpose to enhance the customer experience. With AI, trust is the ultimate currency, and ethical considerations are the key to its success.
Getting Started With Impactful AI
Harnessing AI’s potential is crucial for marketers and product owners. Here are 10 steps to help you magnify personalization, augment business impact and enrich customer experiences:
1. Strategic goals: Set clear AI objectives for personalized experiences and enhanced impact.
2. Data insights: Gather comprehensive customer data from diverse sources for AI analysis.
3. Smart integration: Seamlessly embed AI into your engagement platform or tools for actionable insights.
4. Segmentation mastery: Use AI segmentation to tailor interactions for distinct customer groups.
5. Behavioral understanding: Decode customer behaviors with AI analytics for informed strategies.
6. Predictive precision: Leverage AI predictions to offer personalized recommendations.
7. Content tailoring: Use generative AI for dynamic content creation, such as tailored product suggestions.
8. Effective testing: Utilize AI for A/B testing and optimize campaigns swiftly.
9. Chat excellence: Enhance customer engagement with AI-driven chatbots for real-time assistance.
10. Iterative refinement: Improve AI models based on customer feedback and insights.
Mastering these steps empowers AI-enhanced customer engagement with impactful personalization and enriched customer experiences.
The Future Looks Bright
As AI adoption accelerates, brands have an opportunity to shape their future with an ethical, optimistic human-centric approach. While the path ahead remains unclear, we must embrace this journey with customers at the core.
Insights from AI can foster meaningful interactions and experiences. With intention and care, we can collectively unlock AI’s potential to understand consumers, forge lasting connections and drive sustainable growth. Guided by a human focus, brands can utilize AI to forge deeper consumer connections for the future.
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