ways to boost retention using AI-powered e-commerce personalization strategies
Customer Experience, Customer Value Optimization, Guest Posts

How to Boost Retention using AI-Powered Ecommerce Personalization Strategies

Artificial intelligence is affecting nearly every industry, and the ecommerce sector is no different. In short, the era of AI is here. So much so, that customers today are actively engaging with ecommerce portals that deploy AI solutions without even realizing it.

To top it off, intensive research into the AI-ecommerce paradigm paints a promising picture:

  • According to data by Ubisend, “40% of visitors on an eCommerce site use AI chatbots to find offers and deals.” Plus, it also mentions that “1 in 5 customers is willing to buy from a chatbot.”
  • Research by Mindbowser claims that 95% of consumers believe that ‘customer service’ is going to be the major beneficiary of chatbots.”
  • Saving the best for last, Gartner predicts that 70% of customer interactions will involve technology such as machine learning applications, chatbots, and mobile messaging.”

Clearly, AI is playing an increasingly greater role in driving ecommerce sales and enhancing the user experience – all at the same time. 

6 Ways to Boost Retention using AI-Powered Ecommerce Personalization Strategies  

1. Invest in a Visual Search Feature 

“49% of users say they develop a better relationship with brands through visual search.” – Pinterest

Ever heard of ‘shoppable pins’ with visual search features? That’s the beauty of integrating features that work on visual information more than text. Take Pinterest’s visual feature – Lens – for example:

Often, users wish to buy products they’ve taken pictures of – the catch being, they just don’t know where to begin. Pinterest’s internal research also points towards the same with over 80% of Pinterest users starting with visual search when shopping.”

This is where using innovative visual search features come into play. Here are the benefits of using this feature:

  • Greater convenience: It enables users to upload and search for products whose images they’ve captured in their gallery.
  • Instant purchase: Pinterest will showcase shoppable pins in the visual search results so that users can buy the desired product instantly and without much effort.
  • Enhanced shopping style: Customers claim that using visual search helps hone their style and taste when shopping.

Key takeaway: Long story short, with the use of visual search features, eCommerce businesses can provide unparalleled convenience to customers and elevate the user experience – ultimately drive customer retention as well as loyalty.

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2. Integrate Chatbot for a Personalized Shopping Experience 

While shopping, every customer has multiple queries circling their mind. For instance:

“What is the refund policy for this product?”

“What is the size and dimension of this product?”

“How can I make a payment online?”

You get the drift, right?

In most cases, customers tend to abandon a company if their queries are not addressed instantly and effectively. Enter: chatbots.

You can think of chatbots as handy virtual assistants, ready to serve customers at the latter’s beck-and-call. They’re available 24×7. They don’t take coffee breaks and can handle thousands of queries at one go. They’re advanced enough to offer contextual and relevant information to shoppers today. Let’s look at some real-life examples to understand this better:

  • Lego’s Facebook Messenger chatbot – Ralph is known to drive 25% of the social media sales – thanks to its useful and instant assistance:
  • Another excellent example to consider is Spring’s chatbot, where speed takes center stage with the bot assisting users in finding personalized clothing.

Key takeaway: If you wish to turn conversations into conversions, chatbots are the way to go. It frees up your customer representative’s time so that they can focus on complex problems that the bot cannot handle.

3. Leverage Voice Search for Quick Responses & Reduced Churn

“30% of all searches will be done using a device without a screen.” – Gartner

Alexa, Siri, the examples are many.

Voice search has undoubtedly crept into our lives. If we were to make a comparison, you could think of shoppers as Aladdin and the voice assistants (think: Siri) as the genie. 

Here’s how the process works:

  • Voice assistants today come embedded in your smartphones/smart speakers.
  • All the customer has to do is give ‘orders’ relating to what they wish to buy.
  • The voice assistant will complete the purchase for you or pull up relevant information on how to complete the order in question.

Furthermore, if you wish to optimize your voice search feature, try these tried-and-tested strategies for best results:

  • Focus on drafting information-rich answers
  • Restructure your content on a timely basis.
  • Integrate conversational language to drive relevance and content accuracy.
  • Opt for long-tail keyword phrases and focus on mobile voice search optimization.

Key takeaway: In the case of voice search and optimization, every unique and convenience-led shopping experience is literally a command away! Research by OC&C Strategy Consultants claims that the use of smart speakers is predicted to rise to 55% by 2022.

4. Integrate an All-Powerful AI-Powered Recommender System 

“Retailers that have implemented personalization strategies see sales gains of 6-10%, a rate two to three times faster than other retailers.” – Boston Consulting Group (BCG)

Since we’re talking about Recommender Systems and Ecommerce, it is impossible not to mention Amazon. The ecommerce giant uses this intuitive system to predict customer needs, offer personalized solutions, and do justice to every user’s needs at scale. Here’s a snapshot of the kind of emerging technologies the brand uses:

  • It uses a combination of Collaborative Filtering and Next-in-Sequence models to drive product recommendations.
  • It uses AI for logistical accuracy and efficiency – taking into account factors such as reroutes, changes in delivery and arrival times, among other things.
  • It uses Natural Language Processing for its digitally-powered assistant, Alexa, to engage users in a deeper and more accurate capacity.

How does all this help the ecommerce brand?

  • It enhances product suggestions for users, allowing them to make better decisions:
  • It acts as an informational guide for users, educating them about new products and offers:
  • It optimizes processes and streamlines the workflow:

Key takeaway: Recommender Systems help drive personalization, reduce churn, increase the market footprint, and increase the chances of longer sessions with the users. The ecommerce customer of today demands personalized suggestions from start to finish. It will be cherry on the top if you can also send personalized emails to users based on their viewed and recommended products. 

5. Empower users to “Self-Serve” via an AI-Powered Knowledgebase Software

An AI-powered knowledge base software captures what users search for to deliver customized responses. Simply, this comprehensive knowledge base system houses – and offers – contextual information by using natural language processing to better understand the customer’s request. 

This feature, like the others mentioned above, has emerged more as an expectation rather than a nice-to-have for ecommerce businesses today. Here are its key features at a glance:

  • Indexing siloed information: Ecommerce brands are continuously faced with valuable data from various sources across the enterprise. This data can only be useful if it is delivered to the customers as well as the agents in real-time. This is where a knowledge base comes in handy as it empowers the agents to provide more detailed, intelligent, and intuitive answers.
  • Delivering accurate and dynamic information: In today’s digitally-connected world, static searches are useful to no one. AI offers a helping hand by ranking the most relevant knowledge base articles. That’s not all. It uses past interactions and real-time conversational data to offer on-point information that can help one and all.
  • It allows for a more collaborative working style: By accumulating all the necessary information in one place, a knowledge base allows users and agents to self-serve and work with greater efficiency. It also helps capture recommendations and feedback from all the stakeholders involved to ensure updated and enhanced content.

Key takeaway: All things considered, if you wish to gather insights and leverage an in-depth understanding of your users, invest in a robust knowledge base software right away.

6. Focus on Predictive Analytics for Driving Retention

Predictive analytics is very much the next frontier in ecommerce marketing. This type of analytics is powered by Big Data, Machine Learning, and AI tools. From the ecommerce perspective, it helps to cater to people who have abandoned carts or are at the brink of making a purchase. 

Here are some examples of how predictive analytics works:

  • The brand uses predictive analytics in the form of email marketing to welcome users right at the beginning of the customer’s journey with the brand:

The key learning here is that brands need to collect customer data from the very first interaction and integrate it across every user touchpoint along the way.

Here’s another interesting example to consider:

Notice how the email mentions “Help Us Get It Right” by asking users directly about the kind of content they’d like to receive. Based on the data and preferences the brand receives, the company can further segment the target audience and market better.

Another example of using predictive analytics is to strategically up-sell and cross-sell to existing customers based on their past purchases:

Final Thoughts

Artificial intelligence is driving eCommerce sales and customer loyalty like never before. To sum up, try these time-tested strategies and leverage eCommerce personalization to boost customer retention:

  1. Invest in a visual search feature for greater shopping convenience and enhanced customer retention.
  2. Integrate chatbots for personalized customer experiences and to improve customer retention rates.
  3. Leverage voice search for providing quick responses and reducing churn.
  4. Integrate AI-powered recommender system for reducing churn and increasing the chances of longer user sessions.
  5. Encourage users to go for “self-service” via an AI-powered Knowledge base software.
  6. Focus on predictive analytics for improving customer retention.

Over to you.

Author’s Bio:

Dhruv Mehta is a Digital Marketing Professional who works at Acquire and provides solutions in the digital era. In his free time, he loves to write on tech and marketing. He is a frequent contributor to Tweak Your Biz. Connect with him on Twitter or LinkedIn.

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