Buying Behaviour


Remember a time when salespeople used to go door to door selling products? From then on, technology has grown leaps and bounds only to make buying products convenient, affordable, and cost-saving for consumers. No doubt, all 3 play a crucial role in making our busy lives more comfortable. While on the one hand, we should thank technology but on the other, are we aware of how this is impacting us? Are consumers exploiting the technology, or is technology influencing the consumers? Is AI technology – a boon or a bane? Read on to see if you can arrive at a decision.

In the first series of the article, we understood what AI technology is and saw a quick glimpse of how retailers leverage AI technology using consumer buying patterns. In this article, let us explore the consumer side of the story. How are the e-commerce platforms impacting consumers like you and me?

Research by the World Retail Congress organization (www.worldretailcongress.com) says 35% of google product searches by consumers turn into a transaction in 5 days. India is expected to see the highest online growth rate between 2018-22.  Out of the top five countries with the highest online shoppers, four are in Asia. The E-commerce industry is a hotbed for building wealth in the upcoming years.

Did our Jeff make fair use of it? What happened to his online store? Did Seema move to the online platform to buy milk? If you don’t follow anything I just said, read the first part of the series Artificial Intelligence powering the golden era for Retailers – Part – 1 real quick!

 Trust me. You will enjoy this article much better! 🙂

For those who have read part 1 of AI technology, you would remember how Jeff leveraged the AI technology and built his pricing strategy. Let’s see what happened to Jeff, Seema, and Dinesh in 5 simple scenes like the first part!

Part 1 Conclusion: What happened Jeff after he launched his online store?

We ended part 1 with Jeff launching his promotion campaign for his new online store.

jeff's action plan to implement Artificial Intelligence

Seema grabbed the opportunity and took up a 1-year subscription. Within a month Jeff’s promotion went viral in the neighborhood. Although Jeff sold milk at a lesser price than the price, he sold at his store. His customer base grew to an average of 3,000 active subscriptions. At the end of the year, his sales shot through the roof, and he ended the year earning nearly five times more. At the same time, Dinesh, who was not inclined to move ahead with technology, lost his customer to Jeff, and his sales nosedived to the bottom.

Outcome of Amaze Store New Business Strategy

Did you know? Flipkart website receives around 1.5 billion visits per month and reported a 45% growth in monthly active customers.

Scene 1:  Sunday – Fast forward three years since Jeff opened his online store for selling milk

On a fine Sunday morning, Seema opened the newspaper while going through the technology news section. She was amazed to see “Amaze Online Platform” valued at 100 million dollars, and there it was Jeff in a crisp suit beaming with pride about his flourishing business. Seema took some time to come to terms with what she had just read. The person who sold milk in a small convenience store is now on a newspaper headline with the title “Upcoming Businessman.”

Seema had moved to a different city a year after Jeff opened his online store. After that, she had not followed Jeff’s story until she saw him on the newspaper cover. After reading the newspaper, she got very curious about how Jeff made this happen. She opened her laptop and searched for “Amaze Store Online.”  She discovered that the Amaze store now not only sells essential commodities, but the categories had expanded to electronics, apparel, daily household, and the list went on.

Amaze Online store 3 year journey

Did you know! Flipkart started with 4 lakh funding in 2007 and was valued at 1 Billion at the end of 3 years.


Scene 2:  Sunday- Seema curious to explore other categories to buy online

Seema remembered the convivence of buying milk online. She was eager to check out what “Amaze Online Store” had to offer now. She quickly browsed through some categories, and some dresses caught her attention. She was impressed with the collection and variety “Amaze Online Store” had. She promptly created her login through Facebook ID and added few to Wishlist, hoping to buy them.

After the initial excitement subsided, she pondered over the quality and fit of the dress. No matter how good they looked in the picture, she was not entirely confident about moving the dresses from Wishlist to the cart. She was tired fighting this thought, and finally, she decided to close the browser and get on with her day.

Seema curious to explore other categories to buy online

Did you know!  The E-commerce industry tracks the number of times a person abandons the cart. On average, 7 out 10 people abandon the cart during checkout. 56% of shoppers abandon carts due to hidden costs.

 Retailers and E-Commerce brands lose over $18 Billion in sales revenue each year because of cart abandonment

Scene 3: Monday – Introduction to Nudge theory and Seema typical working day

“A ‘nudge’ is a term used to describe any change in the environment which steers an individual’s behavior predictably while preserving their freedom of choice. It is not a push, nor a shove, but a gentle nudge.”

The following day Seema went back to her work. She had completely forgotten about the dress she wanted to buy.  She opened her g-mail to check her emails, and there she finds an email from the “Amaze Online Store,” asking if she would like to finish her shopping, and in bold, there was a callout saying a 15% discount on the first purchase. There was also an underlying message on her Wishlist products, “Selling Fast.”

Seema was “Nudged” twice if you noticed.

  • 15% Discount to lure her back to the site
  • “Selling fast” message to create a sense of scarcity (Remember, we always value scarce things).

These nudges were enough for Seema to open the site again and move a product from “Wishlist” to the cart. Just when she was about to check out and pay for the dress, she was surprised to see additional add-on costs such as “shipping,” “tax”. These costs were equivalent to discounts provided. Seema was just not convinced about buying the dress. Despite an additional nudge of “10 People looking at the dress” flashing. Seema just abandoned the cart.

Introduction to Nudge theory and Seema typical working day

Did you know dedicated apps from a company called Shopify provides several apps that promise to “Bring Back Shoppers” to complete abandoned transactions?  Some of them allow editing your abandoned cart order and adding in “Free benefit” to reach out again via email reminder.

 Another mind blogging app called “Facebook Pixel Integrator” adds abandoned products from cart to the Facebook tracking list which can be is used by brands and retailers to run Facebook ads to remind the user constantly about the exact item they abandoned.

Scene 4: Tuesday – Seema can’t get the dress out of her head

As compared to the casual browsing on Sunday, Seema had invested a lot of time on Monday thinking she would buy the dress. Unable to completely let go of the thought, Seema opened Instagram casually and was scrolling through the updates. Just when she thought she had forgotten about dress; she sees an ad for the same three dresses with the message “flash sale” Buy 2 to get 30% off! This is a classic “Nudge” tactic to create a sense of “Limited Time Offer.”

Finally, 4th nudge did seem to work. Seema again launches the website to purchase the dresses and be done with it! But there was another message called out on the website shop for “Rs 4,999 and get an Rs 899” worth of dress free + avail free shipping!

Seema was now just Rs. 1,779 away from getting another Rs. 899 worth of free products. She had one more dress in her Wishlist that was “Rs. 1,800”. Precisely the difference amount she needed to get an additional Rs. 899 worth of products.

While Seema was processing all this information, there was “Nudge 6”, Amaze store now was showing all “Affordable Fashion Products from Celebrities” that were available to be shopped within Rs. 1,700/-.

Seema can't get the dress out of her head

Did you know:  Instagram offers e-commerce platform ability to showcase  Ads based on “Location” (of consumers), Demographics, Interests (ads that user might have liked while browsing), Behaviors (based on the activity users are interested), Lookalike Audience (this is scary! Find people like existing customer base) Phew! With our every click, Retailers are hunting us down to find us anywhere from Instagram to g-mail to Facebook to keep showing us the products “we had wished to buy”

Scene 5:  Wednesday – Seema choice validation by peers, influencers, and celebrities

Seema was still feeling overwhelmed by the information and promotion. She decided to put shopping off for a while as she had a birthday party to attend. To Seema’s surprise, her favorite dress that she was thinking of buying, one of the guests was wearing the same dress. She noticed that everyone in the room was talking about her.

The following day, she opens Instagram to see all the photos from the party uploaded to Instagram. Guess what, the girl wearing the dress Seema had liked, received the maximum likes. The comments section was overflowing with compliments.

Seema could not decide if the dress made the girl look beautiful or the complete set of accessories, matching shoes, make up that she was wearing! Social validation is also a kind of “Nudge”. Some other types of these “Nudges” are reviews by influencers, likes, and comments by friends, celebrity endorsements.

Today e-commerce platforms are paying tons of money to Celebrities, to people with the highest numbers of followers, influencers to flaunt their products, and repeatedly keep tagging the brand and posting images of the products on social media.

Seema choice validation by peers, influencers, and celebrities

Did you know: According to the list, Priyanka Chopra Jonas, who, as of July 1, 2020, has 54.3 million followers on Instagram, earns $289,000 (₹2.18 crore approximately) per post. 

So, does Seema finally gives in and shops for the whole look, or does she wake up and realize before she spends more money than she has? If a brand or e-commerce platform can pay Rs. 2.18 crore for a single post. You can only imagine how many people on Instagram, seeing the post by celebrities, are ending up buying the product.

In Summary, the e-commerce industry is thoroughly using consumer behavior data coupled with AI technology to ensure every ad, every nudge message, every promotion on the site gets customers one step closer to sale. And it is working, the reason I say that is because today Amazon has valued 1 trillion dollars, Flipkart at 24 billion dollars, and Jio Retail at 55 billion dollars. The list can go on.

But what about us as consumers, is our earnings growing exponentially? Are we spending more than we are earning due to the e-commerce industry? Are we shopping more than we did a decade ago?  The answer to all and more in the final part of the series! Stay tuned to know how AI technology is driving your purchasing patterns.


From Amazon to upcoming reliance JioMart, e-commerce platforms are riding the golden wave by exponentially multiplying their sales and valuations from billions to trillions of dollars, what is the secret that is powering their growth? How are they capitalizing on the market? How are they able to bring a billion dollars in sales? The answer is “You”, curious how? Read on.

Today, we live in the era where Siri and Alexa (virtual assistants/bots on iOS and Amazon that help answer and perform tasks for you) know more about our choices and routine than our friends and family. Siri and Alexa are a very small part of Artificial Intelligence touted as the 4th industrial revolution that we are experiencing.

Artificial Intelligence is one of the major forces driving many industries towards exponential growth including retail. Research done from Gartner indicates that in 2021 AI augmentation to businesses can create $2.9 trillion business value and 6.2 billion hours of workers productivity [2]

In order to get our head around the trillion-dollar numbers, let’s explore the role of AI in the retail industry.

There are mainly 3 players in the retail industry.

–      Consumers

–      Retailers via brick & mortar stores / Retailers via e-commerce platforms

–      Manufacturers

In part 1 of this article let’s understand what is artificial intelligence and how is it implemented today through a simple story.

What is Artificial Intelligence?

In very simple terms, AI can be broadly described as the ability to predict the occurrence of certain event/task/sale based on the relevant data gathered in the past over a significant period. 

To help you understand this definition better, read a story below that illustrates the impact of AI with help of just one consumer (Seema) who is buying an everyday commodity (Milk) from two different stores (Amaze Store and Dinesh Store)

For ease of understanding, the story is broken down into 5 different scenes:

Scene 1: Observing Seema’s milk buying behavior over a period of 10 days

Carefully, look at the image below and see if you can answer the questions below. Do not scroll down before recording your observation. (No Cheating)!

  1. What does Seema buy every day?
  2. How many kinds of milk does Seema buy and what are the store names?
  3. What time does Seema usually buy milk?
  4. What price does Seema pay to buy the milk?
Seema's Milk Buying Pattern measured by Artificial Intelligence

The questions were easy enough right? Let’s look at the answers now.

  1. Seema buys Milk Every day.
  2. Types of milk: Seema buys either Amul Milk 1L or Goodlife Spl Milk 1L
  3. Store: Seema buys Milk from one of the 2 stores Dinesh Store or Amaze Store
  4. Time: Seema buys milk anywhere between 6:30 am to 10:00 am
  5. Price: Seema pays between Rs 45 – 65/- per day for buying Milk

Got all of them correct?! Good Job!

Now, based on the above data, try the questions below and see if you can predict Seema’s buying behavior for the next 3 days?

  1. What time would Seema buy milk on 28th Aug Friday?
  2. What kind of milk Seema would buy on Sunday 30th Aug?
  3. In which store will Seema buy milk on Saturday 29th Aug?

Although you may have answer popping up in your mind, there still some ambiguity isn’t it? Let me help you here then.

Here is Seema’s buying behavior for the next 3 days.

Seema's Milk Buying Pattern report by Artificial Intelligence

Now, I am pretty sure you were able to answers all the 3 questions above.

Since we now know Seema’s buying behaviour for 10 days, let’s combine both the data points and see if we can better answer the earlier set of questions.

 Deductions based on 6 Days Data Aug 22-27Deductions based on 9 days data Aug 22-28
What Seema BuysSeema buys Milk EverydaySeema buys Milk Everyday
ProductAmul Milk 1L or Goodlife Spl Milk 1LMon-Sat: Amul Milk 1L Sun: Goodlife Spl Milk 1L
TimeBetween 6:30 am to 10:00 am  Mon-Sat: Between 6:30 am to 8:45 am Sun : 10:00 am to 10:10 am
StoreDinesh Store or Amaze Store  Mon-Fri: Amaze Store Sat-Sun: Dinesh Store
PriceRs 45 – 65/- per dayMon-Fri : Rs 45/- Sat : 50/- Sun: 65/-

As you can see, as we got access to more data, the findings became more precise and we can now find a pattern in Seema’s behaviour. This is nothing but learning patterns in the data.

When machine does this job of learning information out of the data that fed into it without human intervention, it is called “Machine learning”. Pretty Cool! Isn’t it?

Scene 2: Reviewing the Store Operations to understand Seema’s buying pattern

Based on Seema’s buying behaviour, can you answer the questions below?

  1. Why does Seema buy Milk from Amaze Store from Mon-Fri and Dinesh Store on Sat & Sun?
  2. Why does Seema pay a higher price for the same milk in the Dinesh store?
  3. Why does Seema buy Goodlife Spl Milk only from Dinesh Store?

The answer is “No”, we don’t know why!

Now, let’s says we were provided with store information below. The answers are now clear, it is simply because the Amaze store is closed on Sat and Sun & Amaze store does not sell Goodlife Spl milk!

Artificial Intelligence Store Information

What we did just now, is to combine 2 different sources of information to understand the reason for certain customer behavior. We now personally know Seema’s reason for her choices, don’t we? The insight that we just found out now is invaluable! You will see why.

The more related data you can find to certain data set, the more powerful your insights will be!

Scene 3:  Is there any relation to Seema’s buying pattern to Stores sales performance?

Let’s take a quick look Store Owner’s profile and their sales performance.

Store Owner Profile and Sales Summary recorded through Artificial Intelligence

Remember the most invaluable insight I mention to you earlier? Now, imagine if Store owner Jeff knew Seema paid a higher price for the Amul 1L milk on Sat? or imagine if Jeff knew Seema went to Dinesh store only because Sham sold one additional product than him?

Scene 4:  Consultant and Data Scientist come to rescue.

Jeff knew if he did not understand the reasons for the drop in sales, very soon he would be out of business. He hired a consultant and data scientist to uncover the problem.

The consultant looked at Jeff’s store and suggested the below solution.

Artificial Intelligence Solutions to revamp amaze store

While bringing up an online store is not a new thing anymore, analyzing customer buying pattern is. This is the job of Data Scientist, the person who can analyze the data to find insights.

If you were to suggest below changes to Jeff based on Seema’s buying pattern, would you agree with the Data Scientist recommendation below?

Artificial Intelligence of buying behaviour

The recommendation above is worth millions of dollars! No amount of worrying and hard work would have helped Jeff improve sales unless he knows what exactly to improve.

This is exactly what Artificial Intelligence is, predicting exactly what price point would interest customer, what products need to recommend to which customer profile? When is the highest probability of converting recommendation into a sale and much more!

All this is possible because companies like Amazon and Flipkart today can store buying patterns of billions of consumers like Seema and then derive insights to improve sales.

Scene 5: Finally, What Strategy does Jeff take after reviewing the recommendation from the data scientist?

Jeff implemented the below plan combining recommendations and his own business tactics.

jeff's action plan based on Artificial Intelligence

What happened to the Amaze store after the changes were implemented did the business sore high or crash down? Did Seema continue to visit Dinesh Stores?  How are giants such as Amazon and Flipkart monetizing the billions of users’ Buying Patterns?

Find out more in Part 2 of this series.