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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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10 Analytics Tools to Guide Data-Driven Design

Analytics are essential for informing website redesigns since they offer insightful data on user behavior, website performance, and areas that may be improved. Here is a list of frequently used analytics tools to guide data-driven design that can be applied at different stages of the website redesign process. 

Analytics Tools to Guide Data-Driven Design

1. Google Analytics:

Use case scenario: Website Audit, Research, Analysis, and Technical Assessment
Usage: Find popular sites, entry/exit points, and metrics related to user engagement by analyzing traffic sources, user demographics, and behavior flow. Recognize regions of friction or pain points by understanding user journeys. Evaluate the performance of your website, taking note of conversion rates, bounce rates, and page load times.

2. Hotjar:

Use case scenario: Research, Analysis, Heat Maps, User Experience Evaluation
Usage: Use session recordings, user surveys, and heatmaps to learn more about how people interact with the website. Determine the high and low engagement regions and any usability problems, including unclear navigation or form abandonment. Utilizing behavior analysis and feedback, ascertain the intentions and preferences of users.

3. Crazy Egg:
Use case scenario: Website Audit, Research, Analysis
Usage: Like Hotjar, with Crazy Egg, you can create heatmaps, scrollmaps, and clickmaps to show how users interact with the various website elements. Determine trends, patterns, and areas of interest in user behaviour. To evaluate various design aspects and gauge their effect on user engagement and conversions, utilize A/B testing functionalities.

4. SEMrush:

Use case scenario: Research, Analysis, SEO Optimization
Usage: Conduct keyword research to identify relevant search terms and phrases related to the website’s content and industry. Analyze competitor websites to understand their SEO strategies and identify opportunities for improvement. Monitor website rankings, backlinks, and organic traffic to track the effectiveness of SEO efforts.

5. Similarweb:
Use case
scenario: Research, Website Traffic, and Demography, Competitor Analysis
Usage: By offering insights into the traffic sources, audience demographics, and engagement metrics of competitors, Similarweb facilitates website redesigns. It influences marketing tactics, SEO optimization, content development, and decision-making processes by pointing out areas for growth and providing guidance. During the research and analysis stage, use Similarweb data to benchmark against competitors and guide design decisions.

6. Moz:
Use case scenario: Research, Analysis, SEO Optimization
Usage: Conduct website audits in order to find technical SEO problems like missing meta tags, duplicate content, and broken links. Keep an eye on a website’s indexability and crawlability to make sure search engines can access and comprehend its material. To find and reject backlinks that are spammy or of poor quality, use link analysis tools.

7. Ahrefs:
Use case scenario:
Research, Analysis, SEO Optimization

Usage: Examine the backlink profiles of your rivals to find any gaps in your own backlink portfolio and possible prospects for link-building. Examine the performance of your content to find the most popular pages and subjects that appeal to your target market. Track social media activity and brand mentions to gain insight into your online reputation and presence.

8. Google Search Console:

Use case scenario: Technical Assessment, SEO Optimization
Usage: Monitor website indexing status, crawl errors, and security issues reported by Google. Submit XML sitemaps and individual URLs for indexing. Identify and fix mobile usability issues, structured data errors, and manual actions that may affect search engine visibility.

9. Adobe Analytics:
Use case scenario:
Website Audit, Research, Analysis,
Usage: Track user interactions across multiple channels and touchpoints, including websites, mobile apps, and offline interactions. Segment users based on demographics, behavior, and lifecycle stage to personalize marketing efforts and improve user experience. Utilize advanced analytics features such as path analysis, cohort analysis, and predictive analytics to uncover actionable insights.

10. Google Trends:

Use case scenario: Content Strategy, Keyword Research, User Intent Analysis
Usage: For competitor analysis, user intent analysis, and keyword research, Google Trends is used in website redesigns. It helps in content strategy, seasonal planning, SEO optimization, and strategic decision-making. It directs the production of user-centric content, increasing traffic and engagement, by spotting trends and insights.

About the Author:

Vijendra is currently working as a Sr. UX Designer at Mantra Labs. He is passionate about UXR and Product Design.

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