How brands can drive personalization at scale

In the third year of a global pandemic, consumers want companies to be more empathetic. In response, brands are aligning more closely with changing consumer preferences. To deliver a superior customer experience, we see several B2C brands investing in technologies that enable personalization. But doing this on a large scale, with millions of consumers, is quite a challenge. Conversational AI helps brands find their way.

Conversational technology solutions are improving to deliver a unified omnichannel experience. Brands can design natural, human interaction journeys for consumers to engage anytime, anywhere. For example, brands are using personalized profiles to access consumer details and monitor preferences quickly and easily. Micro-chats via voice, video, or text enable personalized recommendations to consumers at every stage of brand engagement.

Why bots are our new best friends

Using conversational AI-enabled virtual assistants, brands can interact with consumers and understand, as well as respond accurately, with little to no human dependencies. With data-driven profiles developed for each consumer, virtual assistants can effectively identify pain points and recommend an appropriate solution in seconds. Through ongoing training, these assistants improve their effectiveness and learn better from consumers’ past interactions with the brand, past purchases, wish lists, questions, and more.

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Conversational AI is transforming businesses across industries

Brands using conversational engagement technologies are seeing increased brand loyalty and increased sales across all industries. In BFSI (banking, financial services and insurance), a digital approach to conversational AI can help brands use the power of personalized messaging to create better support experiences. From account setup, upgrades, promotions, FAQs and transactions to recommendations on which financial products are best suited to the consumer’s profile – automation is key.

In retail and e-commerce, customers seek expert guidance in product discovery and selection with intelligent preference-based recommendations – across touchpoints during the buying journey. Tata CliQ is a good example. By sending personalized messages and offering to more customers via WhatsApp, the digital lifestyle brand saw its return on investment increase 10 times, recording sales of $500,000 in just one month. With increased click-through and conversion rates, Tata CliQ is now looking to expand its conversational engagement game to reach and connect with more consumers. Using a combination of data science and WhatsApp, the brand could personalize communication and customer engagement for a large customer base.

In healthcare, virtual assistants can engage with customers to manage appointment bookings and changes, FAQs, prescription reminders, allergy lists, and personalized assistance around the clock and 7 days a week. These are personalized for each patient so that messaging communication is targeted towards resolving their specific issues. Healthcare providers use platforms such as WhatsApp, Facebook Messenger and web chat to share critical patient updates and provide personalized patient care through their smart devices.

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New-era companies are doubling down on conversational AI for growth

In addition to conventional industries, we are seeing several new era companies from sectors like EdTech, Realty, and many others turning to conversational engagement technologies for faster growth and expansion.

Take the case of Doubtnut, an EdTech platform helping students improve their knowledge in STEM subjects. Previously, students had to post photos of their questions on the Doubtnut website or mobile app. But Doubtnut soon realized that limited access to high-speed mobile internet connectivity in the suburbs was impacting its service. Now, thanks to a smart WhatsApp chatbot, students share their doubts via WhatsApp and get links to videos with answers, in their preferred language, in about ten seconds. Doubtnut recorded a user satisfaction rate of 95% and daily users increased by 224%. And Doubtnut’s tutor-student engagement rate has increased by 260%.

NoBroker, an online real estate listing platform, is another good example. Previously, to list their property details and add photos, less tech-savvy clients had problems uploading photos to NoBroker’s website and mobile app. This required the NoBroker team to contact clients offline, gather photos and upload them centrally – a tedious, staff-intensive and unproductive process that resulted in overhead costs. Now, using NoBroker’s smart WhatsApp chatbot, owners can interact and upload photos directly through WhatsApp, as well as send photos to a family member or friend on the platform. Property listing time – especially for uploading photos – went from three days to around six minutes or less. NoBroker saw a 20x annualized return on investment along with a 2.8x increase in real estate transactions.

The future of customer experience is conversational

More and more customers are now looking for direct messaging and interaction with their favorite brands for real-time problem solving and support. They want to buy from a brand that provides highly personalized recommendations and suggestions.

We find that most companies use a patchwork approach to conversational AI. They typically use one technology provider for messaging, another for voice, and perhaps another for analytics and customer service. This leads to integration, security, and performance issues. In the process, the customer ends up with an inconsistent brand experience. A holistic conversational AI strategy is the key to transformational growth.

In summary, conversational AI helps brands democratize every consumer’s experience with hyper-personalization, richer interaction, and greater accessibility. Is your brand armed with a next-gen conversational engagement platform to succeed in the conversational economy?

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