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Share some of the top trends in customer engagement. How are these trends impacting businesses?
Customer engagement has been quite dynamic in the last few years, especially following the pandemic outbreak. In response to the uptick in e-commerce, brands are pivoting to omnichannel operations irrespective of customer or business-facing models. Existing brick-and-mortar strategies are being revamped to integrate online commerce, leading to multi-channel experiences from brands.
The growing traction of e-commerce and omnichannel models has levelled the playing field, allowing new entrants to gain market share through competitive and unique value propositions. For incumbent brands, that scenario emphasizes customer retention — known to increase profits while costing significantly less than new acquisitions.
Meanwhile, high consumer awareness has shaped an experience economy, where goods and services are best sold by communicating their positive impact on buyers’ lives. As each customer can harbour different opinions about what constitutes value, businesses are required to personalise their offerings, recommendations, messaging and overall engagement.
What are some of the challenges facing businesses in customer engagement? How are you helping businesses overcome these challenges?
As each customer exhibits unique preferences and ascribes value to different services or price points, brands cannot have a one-size-fits-all approach; personalisation is key. However, personalised engagement across multiple channels can be challenging, especially for brands with a massive operational scale.
At the same time, due to high awareness of different options and value propositions in the market, customers are susceptible to churn. In other words, the slightest disengagement and negative experience can make customers turn away from a brand.
Fortunately, exposure to digitalisation has enabled brands to build a repository of customer data, which can be harnessed to derive insights using AI analytics. The valuable information pertaining to individual shopping behaviours and preferences can be used to accurately segment the audience for marketing campaigns. In conjunction with journey designers and other campaign orchestration tools, marketers can hyper-personalise customer interactions across touchpoints.
Today, it is becoming increasingly important for companies to have a full-stack solution with all the above capabilities and tools for effective customer engagement — a market need that we are catering to.
How does customer happiness lead to improved customer retention and loyalty, and what strategies can businesses employ to enhance customer happiness?
When a brand truly understands customers’ requirements and exceeds expectations, it successfully onboards them. If the brand stays consistent with its messaging and service/product quality and adapts to customers’ evolving expectations, it garners their loyalty and trust. That, in turn, translates to long-term relationships and a good retention rate. However, a happy customer tells a friend; an unhappy customer tells the world. Therefore, brands must not get complacent with existing customers and their experiences.
AI-driven solutions like our retention operating system specialise in not only delivering consistent experiences to customers but also course-correcting engagement strategies through deep-learning models. Such agility is possible by harnessing first-party data and adopting a human-centric approach to engaging customers and addressing their pain points.
In what ways can AI and machine learning be utilised as cornerstones to define and enhance customer experiences? How can these technologies be constructively employed to improve customer journeys and personalise interactions on a tech platform like Webengage?
The pandemic and the reactionary pivot to online ways expedited digital transformation by years. Overnight, consumers were met with new channels and options. So, in the last couple of years, shopping behaviours have been in a state of constant flux. Though such shifts have now abated, behaviours will continue to evolve with the emergence of new technological frontiers like Web3. Under that scenario, AI-based models are the best bet for brands to stay in sync with customer movements.
In our retention operating system, AI algorithms analyse customers’ behavioural data and requests in real-time. Integrated with CRM and other software, such algorithms automatically initiate appropriate responses. Such machine-based actions can be accomplished at scale and with efficiencies that transcend human capabilities. In other words, AI can personalise and enhance customer experiences with minimal human intervention while maximizing savings and ROI.