The whole world, in general, has made a massive shift to online and the internet in the 21st century and everything we do online creates data. It must not come as a surprise to anyone that we in general create massive amounts of data on a daily basis. According to one of the reports by IDC, it is estimated that the digital universe of data will grow over 175 zettabytes by 2025.
One industry that will heavily contribute to this number is e-commerce. This world of e-commerce has millions of data points which we access via channels like social media activity, geolocation services, web browser histories, device and browser information, to name a few.
Of course, gathering data is the first step to deeply understanding your customers but analyzing this data is what does miracles – especially when it comes to e-commerce and D2C businesses. E-commerce companies have tried to understand their customers’ purchase behavior and tailor their business efforts accordingly for over a decade now. However, there is still a big gap and a lot can be done to utilize this gold mine of data in the best possible manner.
Now that we are discussing data in e-commerce, let us also briefly talk about the power of personalization in e-commerce. After all, they are closely interlinked, aren’t they? Imagine if you as a shopper get a tailored experience according to your likes/needs every time you shop online? Think Spotify for online shopping!
E-commerce as an industry has been on the hunt for this holy grail of personalization for some time – a consistent, cross-channel experience that adapts to customer needs and goals in real-time. This however is beyond the reach of most e-commerce businesses. How can we enable all online sellers to provide a world-class personalized shopping experience to their customers? We will discuss all this in detail now. Let’s get started!
The Era Of Data-Based Decisioning
Jim Bergeson rightly quotes, “Data will talk to you if you are willing to listen.” And for the love of data, I cannot deny this at all. The value of the massive data available can only be created if meaningful insights can be drawn out from this data and then utilized in our decision-making. That’s the power of data science and it truly is a superpower waiting to be utilized across e-commerce.
We are living at a time where you can literally predict your customer’s next move on your shopping website and enhance their shopping behavior in real-time. For instance, let us assume that you run an e-commerce store that specializes in antique jewelry. Now in your analytics dashboard, you can see that a customer is looking for stone embedded rings. They add one of the rings to their cart and proceed to checkout. They choose net banking as a payment option and due to some technical errors, the payment could not get through. Now, you can leverage data and disable net banking from the payment window in real-time. Instead, highlight the payment modes experiencing the highest success rates on top and make the checkout process easier for them thus increasing conversion rates.
This is just one minor example of how data can do wonders for your business. There are hundreds of different ways in which you can leverage data to enhance the overall shopping experience for your customers. I have picked up a couple of references to understand how.
#01 Understanding your customers’ shopping behavior
Data can help you with insights like what are your prospects’ preferences and what time they usually shop. You can map the details out and ensure that your tech, support, and offers are all up and running during prime time!
For example, by knowing the time of shopping of your customers, you can send them offer-related or new collection messages during that time to enhance the shopping experience.
#02 Leveraging customer support
E-commerce businesses can use data to track customer service experiences, like showing how fast your response times are — which plays a huge factor in customer service. Data can also be used to track delivery times and customer satisfaction levels. This helps companies identify the potential problems right in time before the customer creates noise on public forums.
For example, if an order is stuck in an in-transit location for more time than expected, a real-time trigger can be set up. This will notify the operations team who can then check with the shipping partner on what the issue is and resolve it. Similarly, the same information can be relayed to customers informing them of the delay and the reason for it.
#03 Providing personalization to customers
Data can help e-commerce businesses by giving insights on customer behavior and demographics, which is useful in creating personalized experiences. In fact, according to a report, 87% of shoppers said that when online stores personalize the shopping experience, they are driven to buy more.
Some examples of this case are:
- Determine the product line that customers are likely to buy, along with the sizes and fit that is suitable for them
- Target product recommendations and promotions to relevant customers
- Automatically changing the language of the website depending on the customer’s preferences
Data As A Tool To Improve E-commerce Conversions
While we all broadly understand the applications and implications of data, it is important to understand its value at every step and how it can help improve conversion rates throughout the funnel.
#01 Source Identification: A lot of shoppers abandon the cart at the last moment due to ambiguity in the delivery time. With the powerful mechanism of geofencing and location services, it has now become accessible to find the location of your prospects and your customers. You can calculate the delivery time for their location and inform them while they are shopping – this enhances the overall customer experience and in the long run, boosts conversion rates.
#02 Person Identification: Understanding identify details like their gender, nationality, preferred language, and basis their details offering them customized user journeys will definitely boost conversions. You can offer them an option to switch languages, enhance their search results by prioritizing what they like, and change the currency value as per their location.
#03 Address Identification: Address plays an important role in the e-commerce industry. One of the biggest challenges, RTO has highlighted the use of fraudulent addresses or incomplete addresses that add to the burden of the logistics providers. Use data to look for the shopper’s previous shopping behavior and accordingly hide or show CoD as a payment option.
#04 Payment Journey: A lot has been spoken in the industry about the advancement of digital payments. That’s right. But even after that, there is a lot of scopes to improvise on the payment journey. Emphasizing a truly one-click checkout, pre-filled information, and highlighting frequently used payment options are some ways to get started!
#05 Post-order Journey: One of the areas that are still left untouched by a majority of the budding e-commerce business is the post-order journey. Post-order journey means keeping your customer updated about the movement of their order at every step, confirming their presence at home, and handling CoD orders the right way.
The Miracle Of Predictive Analytics in e-commerce
Predictive analytics, a category of data analytics, is an intelligent technology that analyzes current and historical data to uncover insights, assess dependencies between numerous factors and discover patterns for predicting future outcomes. While data-based decisioning is the first part of the puzzle, predictive analytics is where it truly becomes revolutionary. Predictive analytics can help in both personalization to drive e-commerce conversion rates as well as in predicting supply chain movements and RTO.
Here’s how predictive analytics can help you:
- Determine the product line that customers are likely to buy next, along with the price that the shopper will agree to pay for it
- Target product recommendations and promotions to the right customer
- Predict estimated date of delivery depending on shopper’s address and display the same to set the right expectations and ensure a good shopping experience
- Predict the customer’s intent and predict order riskiness and RTO probability
So yes, these are truly exciting times but I want to emphasize the responsibility that this kind of data brings with it. The Paramount Importance of every business out there should be on ensuring that all data is used only and only for improving customer experience and nothing else.
Solving RTO via Predictive Analytics
I am sure you are aware of what RTO or Return to Origin is and how this is an Indian-specific e-commerce problem because of the “Cash on Delivery Payment method”. In my journey of understanding e-commerce and the increasing numbers of RTO it brings with it, I have understood that the major reason for RTO is dwindling customer intent. A customer places an order for a product they like at some point in the day via CoD. 3 days into the order and they realize that they do not really need the product. However, they forget to cancel the order, largely because they are aware of the return policy and they haven’t paid yet. Now, on the day of delivery, the customer tells the person that they do not need the order anymore.
To back this up with data, RTO in Cash on Delivery purchases hovers between 30-40% whereas in PrePaid transactions it is 1-2%. Oh yes, you read it right. That’s how big the difference is. But guess what, in general even for established e-commerce marketplaces and brands, their CoD % is greater than 70%! RTO losses hence become very significant to e-commerce businesses.
This needs to be solved and predictive analytics can play a huge role here. Using purchase intent signals during checkout and historic data of compulsive RTOers, we can build predictive models to assess the riskiness of order in real-time. A risk score along reasons can be populated which can be used to effectively reduce RTO both during checkout and during the post-order journey.
For example, if a customer ordering on your site is highly risky based on his/her shopping behavior and historic data, we can disable Cash on Delivery by the time the customer reaches the payment screen. Similarly, any delays in shipping, the exact date of delivery, and other supply chain-related events can be predicted. Using the information, constant and personalized communication can be established with the customer to maintain intent post-purchase. These are just the tip of the iceberg and I believe RTO can be truly brought down to manageable rates with predictive models.
Enter Gokwik – A Partner Every Business Needs
All this while I have been talking about the importance of data in e-commerce. I wonder if you thought about what made me start ‘GoKwik’ along with Chirag.
Something very surprising is that even after all this time while having tons of data points on the shopping behavior of customers at our disposal, we have not been able to carve a tailored experience to provide the best shopping experience, increase conversion rates and reduce losses like RTO. In fact, most of the booming e-commerce businesses are missing out on growth because they can’t invest in personalization and other data/tech capabilities.
Being pioneers in the industry, the established brands have been blessed with powerful tech capabilities that are built in-house. It is about time that the booming e-commerce businesses also get a chance to enjoy what they have. That exactly was the problem statement that motivated me to get my hands on democratizing e-commerce.
Now, are you wondering what is at GoKwik up to?
In two simple words, I would say ‘democratize e-commerce’. But honestly, that would not do justice. Being a data aficionado myself and knowing about the potential data holds, I aim to bring about a change in the way the e-commerce industry perceives data. I have a thing for SMBs – that they deserve powerful platforms that can help them scale fast and better by utilizing the powerhouse of data. Oh while we are at this, I have just one ethic on this journey – responsible data handling without a pinch of misuse so that while we scale businesses, we ensure we do not cause harm to humanity. Yeah, that’s pretty much it!
If you are an e-commerce brand looking for higher conversion rates and reducing RTO by using data effectively, write to me at firstname.lastname@example.org Let’s come together and do data-based miracles!