By Sonakshi Nathani
In today’s crowded direct-to-customer (D2C) marketplace, a brand hoping to stand out from its competition needs to create a connection with its audience. The best way to achieve this is by driving conversations. The fact that conversations help build trust and lead to higher conversion rates has long been common knowledge in the traditional sales space. Conversation-driven personal selling techniques strengthen relationships with prospective customers, enhance brand credibility, and enable reps to communicate key value propositions more effectively.
However, this technique is only feasible up to a certain point. Scaling it beyond that becomes an unviable and cost-ineffective investment. This is especially true in the digital era, in which brands with an online presence will receive thousands of customer queries a day. For example, imagine the number of employees leading D2C businesses like Lenskart or Mamaearth would require to hold a conversation with every interested customer. It simply isn’t possible.
The implementation of new technologies, such as conversational commerce and bots, presents a solution to this issue. Conversational commerce is the use of live chats and chatbots by brands to interact with customers. This includes providing details of services, aiding in transactions, and providing post-sale services and assistance. These chatbots are powered by conversational artificial intelligence (AI) and equipped with machine learning (ML) and deep learning (DL) capabilities. This enables chatbots to hold extended conversations with users, provide context-specific responses, and engage interested audiences in-depth and at scale, something that’s never previously been achievable.
Leading online marketplaces such as Amazon have spent years improving their chatbot capabilities to better automate their online channels. By integrating functions such as natural language processing (NLP), their AI-powered bots help drive sales by improving search functionalities and streamlining customer relationship management (CRM) functions.
Amazon and other major e-commerce marketplaces are important to the success of D2C brands, driving over 50 percent of their sales volume. This is extremely helpful to D2C businesses. But it is important to remember that any customer loyalty will be to the platform through which the purchase is made, and not to the individual brand. That means that if a competitor offers a better price on a product, the customer will have no hesitation in switching over. Once that happens, there is no way for the brand to re-engage customers.
Brands that opt to rely exclusively on existing online marketplaces need to bear in mind the downsides of this approach. For example, Amazon charges sellers on its platform between six to 45 percent of each product’s selling price, with the average seller paying about 15 percent of the total sales cost as a fee. This means the ultimate margins are significantly worse on any product sold through the platform.
In order to compete and build their own customer pool, D2C brands need to provide more personalised and differentiated experiences than those available on such marketplaces. This hinges on the effective implementation of tools such as AI and conversational commerce, which when combined can make for predictable buyer experiences. This can be achieved in the following ways:
The role of AI in content curation and marketing
Content is the lifeblood of social media. The most effective way for a D2C brand to stand out on social media platforms and attract new customers is through fresh and topical content. This is a cost-effective route for brands that lack the marketing budgets of their larger peers.
Effective content marketing strategies have been shown to generate up to three times more leads than traditional marketing methods. The implementation of AI allows marketers to generate fresh ideas, pinpoint trending topics, and streamline content creation. Furthermore, it allows marketers to distribute content in the most impactful and systematic manner.
Identify and segment potential customers
A brand looking to maximise its consumer base will identify multiple diverse groups to target as part of its outreach. Identifying and segmenting prospects based on demographics, interests, or behaviour is a complex task that is both time and resource intensive. The integration of AI and ML can boost this process, rapidly identifying various categories across platforms and curating a quality list of prospects. Using these profiles, conversational commerce and AI-enabled chatbots can drive personalised conversations most likely to result in sales to new and existing customers.
Respond and engage with repeat customers
Most D2C brands rely on repeat purchases from their buyers. That is the flywheel that powers their revenues. Buyers need to interact with brands to further improve their product and delivery experiences, and this process can be enhanced by conversational commerce. Insights collected from previous purchases and interactions using AI can be used to deliver personalised messaging to return shoppers at the appropriate time. Using this information, the chatbot can interpret a conversational user query and provide an appropriate response. The end result is that the user receives a customised response with no waiting time. About 82 percent of users report feeling positive about a brand after reading content personalised to them, and this can be amplified to build brand loyalty with existing customers.
The author is the co-founder of Bikayi
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