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10 Chatbot Strategies eCommerce Brands Use to Boost Sales In 2023

By :

Online shopping isn’t just about silent category browsing. It is about customer communication first. Hearing and in-time guiding customers at each step of their journey is key to sales growth. 

Sounds like a task for a 24/7 customer service team, heh? It’s a good thing that a chatbot tool for business can automate part of these processes. 

Moreover, 40% of shoppers are ready to use it. Tommy Hilfiger is one of the many brands that use that knowledge. Its chatbot brings the brand an 87% rate of returning customers. Another case is the Just Eat chatbot, with a 266% conversion rate.

Intrigued? There are more examples in the article! Find out ten chatbot strategies eCommerce brands use to convert customers on websites, messengers, and social media 👇

24/7 assistance on FAQs 

Imagine a never-sleeping support manager answering repeating customer queries around the clock, with no vacation or coffee break. 

It is an automated chatbot. Think about such an employee when building your customer service 😉

Launch it and:

  • Provide visitors with instant self-service at any time. 
  • Save budget by focusing managers’ time on solving high-priority issues.

Example from the Hitee chat👇

In addition to simple questions, this FAQ chatbot can provide customers with information about insurance options.

Notify consumers about new products

This case is popular in fashion and luxury retail. Instead of mainstream emails, they talk about new collections in messengers. And for a reason! For instance, compared to the 25% Open Rate of email, Facebook has an impressive 80%.  

Thus, when the new collection is live, its subscribers see +1 in DMs. It is a company chatbot telling customers about new items in stock. Casually and cheerfully, it engages them to browse for more pieces directly in a messenger without switching to a website. 

Example from Burberry👇

This luxury retail brand implemented a Facebook Messenger chatbot to introduce customers to their latest collection of bags.

A chatbot by Burberry on MessengerImage source.

Recommend products

The ability to generate endless chatbot ideas makes it an ideal tool for businesses. And this scenario is a good confirmation of that. Launch a chatbot that will define customers’ preferences in an up to five-question dialog. 

Examples of product recommendations from Lego👇

The company launched Ralph the Gift Bot to help its customers choose the perfect gift: 

Process orders 

Allowing customers to order in a chatbot is a great idea to save your managers time and follow the introverts’ desire to avoid direct communication. 

Here is how it works. Customers choose an item and place an order without leaving a chat. For this, people share personal details like name, telephone number, and billing address, and a chatbot will route them to the checkout page on a company website. 

An example from the 1-800-Flowers store

In addition to the gift choice, its users can also submit their order information. A chatbot is like your inbound lead conversion administrator who collects recipients’ addresses, names, and phone numbers, billing addresses and only then routes them to a website checkout page.

Finally, the best thing here – to make the customer experience better, the chatbot offers to save this data.

Tell about sales and promotions

Enhance your sales campaign with a proactive chatbot message. Choose a segment you want to send it to and launch a personalized offer, for instance, 20% off on a new dress collection for customers who visit relevant store categories. 

As for the conversation scenarios, there are two options:

  • Showing products on sale and routing to a checkout or shopping cart.
  • Offer personalized recommendations of items on sale.
  • Capturing customers’ emails in exchange for a coupon.

Here is an example of how it can work 👇

This chatbot engages customers with a bright image, and then shares coupon codes.

Recover shopping carts

70% of online buyers leave items in their carts instead of buying. The fix?

  • Launch a website chatbot to engage visitors when they are trying to leave.
  • Launch a messenger or social media chatbot to re-engage those who left. 

E-commerce marketers switch to this strategy because of the low Open Rate of the classic follow-up emails and the high price of the SMS channel. 

An example of a cart-recovering chatbot 👇

Perfuel Pet Suppliers sends follow-ups in a Facebook Messenger chatbot for registered customers who left the store without a purchase. 


Image source

Upsell and cross-sell

Depending on the product page customers visit, or their shopping cart, a chatbot can suggest additional products or upgrades.

Here is an example of how it works on Shopify👇

When a customer is on a particular product page like jeans, in some time a chatbot message appears “I see you eyeing our new black Levis jeans..” and offers to discover matching items.

Gobot eCommerce Chatbot
Gobot eCommerce Chatbot

It is a great example of how businesses transform customer experience and personalize it. 

Help customers track orders

In a short conversation, a chatbot will define the issue, capture the order number, and share its status instantly. All you have to do is to integrate it with the logistics system. 

Order tracking chatbot example👇

MR.DIY, a Malaysia-based home improvement retailer, launched such a chatbot for its website visitors. In real-time, the chatbot delivers information on where is a customer’s order: 

It brought MR D.I.Y an 80% growth in its containment rate. 

Collect customers’ feedback

There are several challenges that e-commerce businesses face when trying to gather customer feedback:

  • A low response rate of the marketers’ attempts to get customers’ feedback via email.
  • Customers post negative feedback on socials or review websites.
  • A lot of time is spent collecting, managing, and analyzing customer feedback. 

The fix? Automate the process with a chatbot.

For example, contact them on checkout after the payment or after a conversation with a customer manager. 

For example 👇

You can send a short survey with stars and a comment field or turn the process into a conversation by reacting to the rating the customer gave you.

Image source.Image source.

Engage customers in the loyalty program

Use a chatbot to automate the way you:

  • Engage customers to join your loyalty program.
  • Register them.
  • Provide loyalty points updates.
  • Suggest rewards they can redeem.
  • Answer FAQs.

Loyalty program chatbot examples 👇

The first case is about loyalty program registration. The chatbot collects customers’ contacts and promises to notify them about discounts.

Image source.

The second is about points updates and announcements. It actually does what the first promised – send loyalty program updates and engage to continue shopping.

To sum up

Inspiring examples, right? When correctly set up, chatbots provide personalized interactions, resolve queries swiftly, and bring you an army of loyal customers. But to make any examples work in your business, mind the following rule – segment and personalize its workflow with the info about customers’ behavior and preferences. 

About the Author: Evelina Carillo is a friendly and skilled writer and blogger with more than a decade of experience in crafting all sorts of content for the marketing and business world. She’s also spent five years diving into the exciting world of EdTech, where she’s continued to learn and grow in her field.

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Will AI Be the Future’s Definition of Sustainable Manufacturing?

Governments worldwide are implementing strict energy and emission policies to drive sustainability and efficiency in industries:

  • China’s Dual Control Policy (since 2016) enforces strict limits on energy intensity and usage to regulate industrial consumption.
  • The EU’s Fit for 55 Package mandates industries to adopt circular economy practices and cut emissions by at least 55% by 2030.
  • Japan’s Green Growth Strategy incentivizes manufacturers to implement energy-efficient technologies through targeted tax benefits.
  • India’s Perform, Achieve, and Trade (PAT) Scheme encourages energy-intensive industries to improve efficiency, rewarding those who exceed targets with tradable energy-saving certificates.

These policies reflect a global push toward sustainability, urging industries to innovate, reduce carbon footprints, and embrace energy efficiency.

What’s driving the world to impose these mandates in manufacturing?

This is because the manufacturing industry is at a crossroads. With environmental concerns mounting, the sector faces some stark realities. Annually, it generates 9.2 billion tonnes of industrial waste—enough to fill 3.7 million Olympic-sized swimming pools or cover the entire city of Manhattan in a 340-foot layer of waste. Manufacturing also consumes 54% of the world’s energy resources, roughly equal to the total energy usage of India, Japan, and Germany combined. And with the sector contributing around 25% of global greenhouse gas emissions, it outpaces emissions from all passenger vehicles worldwide.

These regulations are ambitious and necessary. But here’s the question: Can industries meet these demands without sacrificing profitability?

Yes, sustainability initiatives are not a recent phenomenon. They have traditionally been driven by the emergence of smart technologies like the Internet of Things (IoT), which laid the groundwork for more efficient and responsible manufacturing practices.

Today, most enterprises are turning to AI in manufacturing to further drive efficiencies, lower costs while staying compliant with regulations. Here’s how AI-driven manufacturing is enhancing energy efficiency, waste reduction, and sustainable supply chain practices across the manufacturing landscape.

How Does AI Help in Building a Sustainable Future for Manufacturing?

1. Energy Efficiency

Energy consumption is a major contributor to manufacturing emissions. AI-powered systems help optimize energy usage by analyzing production data, monitoring equipment performance, and identifying inefficiencies.

  • Siemens has implemented AI in its manufacturing facilities to optimize energy usage in real-time. By analyzing historical data and predicting energy demand, Siemens reduced energy consumption by 10% across its plants. 
  • In China, manufacturers are leveraging AI-driven energy management platforms to comply with the Dual Control Policy. These systems forecast energy consumption patterns and recommend adjustments to stay within mandated limits.

Impact: AI-driven energy management systems not only reduce costs but also ensure compliance with stringent energy caps, proving that sustainability and profitability can go hand in hand.

2. Waste Reduction

Manufacturing waste is a double-edged sword—it pollutes the environment and represents inefficiencies in production. AI helps manufacturers minimize waste by enhancing production accuracy and enabling circular practices like recycling and reuse.

  • Procter & Gamble (P&G) uses AI-powered vision systems to detect defects in manufacturing lines, reducing waste caused by faulty products. This not only ensures higher quality but also significantly reduces raw material usage.
  • The European Union‘s circular economy mandates have inspired manufacturers in the steel and cement industries to adopt AI-driven waste recovery systems. For example, AI algorithms are used to identify recyclable materials from production waste streams, enabling closed-loop systems. 

Impact: AI helps companies cut down on waste while complying with mandates like the EU’s Fit for 55 package, making sustainability an operational advantage.

3. Sustainable Supply Chains

Supply chains in manufacturing are vast and complex, often contributing significantly to carbon footprints. AI-powered analytics enable manufacturers to monitor and optimize supply chain operations, from sourcing raw materials to final delivery.

  • Unilever uses AI to track and reduce the carbon emissions of its suppliers. By analyzing data across the supply chain, the company ensures that partners comply with sustainability standards, reducing overall emissions.
  • In Japan, automotive manufacturers are leveraging AI for supply chain optimization. AI algorithms optimize delivery routes and load capacities, cutting fuel usage and emissions while benefiting from tax incentives under Japan’s Green Growth Strategy.

Impact: By making supply chains more efficient, AI not only reduces emissions but also builds resilience, helping manufacturers adapt to global disruptions while staying sustainable.

4. Predictive Maintenance

Industrial machinery is a significant source of emissions and waste when it operates inefficiently or breaks down. AI-driven predictive maintenance ensures that equipment is operating at peak performance, reducing energy consumption and downtime.

  • General Electric (GE) uses AI-powered sensors to monitor the health of manufacturing equipment. These systems predict failures before they happen, allowing timely maintenance and reducing energy waste.
  • AI-enabled predictive tools are also being adopted under India’s PAT scheme, where energy-intensive industries leverage real-time equipment monitoring to enhance efficiency. (Source)

Impact: Predictive maintenance not only extends the lifespan of machinery but also ensures that energy-intensive equipment operates within sustainable parameters.

The Road Ahead

AI is no longer just a tool—it’s a critical partner in achieving sustainability. By addressing challenges in energy usage, waste management, and supply chain optimization, AI helps manufacturers not just comply with global mandates but thrive in a world increasingly focused on sustainability.

As countries continue to tighten regulations and push for decarbonization, manufacturers that embrace AI stand to gain a competitive edge while contributing to a cleaner, greener future.

Mantra Labs helps manufacturers achieve sustainable outcomes—driving efficiencies across the shop floor to operational excellence, lowering costs, and enabling them to hit ESG targets. By integrating AI-driven solutions, manufacturers can turn sustainability challenges into opportunities for innovation and growth, building a more resilient and responsible industry for the future.

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