Why Customer Analytics is Important for Ecommerce?
Contributed by: Sanjay G.
There is a lot that goes into building a successful and impactful e-commerce business. Customers are a very critical pillar of any business, especially in an environment where so many choices are available to customers, and the cost of switching is zero.
However, customer analytics helps understand the customer’s needs and their behaviour that can be achieved by tracking some of the key metrics and implementing simple but targeted strategies. Once you are tracking the correct data and metrics, you can start using the resulting customer insights to inform business decisions and improve acquisitions, retention and loyalty.
Good leadership must have a different strategy to grow its customers in all segments – to execute these strategies efficiently; We need to understand customer analytics from all aspects. Here we’ll look at what customer analytics is all about and what makes it so crucial for e-commerce companies.
Active Customer Base
First of all, you must realize that your total customer base is not your active customer base. There is a significant chunk of customers who have lapsed and have not used your platform in recent times; such chunk of your total base is called “inactive customer base” or “lapsed customer base”.
A customer who has used the platform or service in recent time can be considered an active customer and is highly likely to return. The duration for which a customer shall be considered active depends on the kind of service or product available on the platform. For example – A grocery selling platform may consider users active just for several weeks to a month, while an e-commerce company selling apparels may consider this duration as several months.
A top percentile of your loyal customer base is actually very important because they are not just the customers. They are the brand advocates. They refer the brand to their connections simply based upon their excellent experience in the past. This chunk of customers should be identified and given some rewards to further encourage them.
The active customers are highly likely to return to your platform, and two things matter the most while tracking the repeat potential of your customers:
1. The % of customers repeating and the frequency at which these customers are repeating (latency)
2. Month over month new acquired customer % vs repeat customer % (Behaviour of Consumers)
Extending the study of the behaviour of repeat consumers using customer analytics, one should be aiming to find the answers to these key questions
- Why would any user convert to become a customer on my platform?
- What can make that user come again for his/her next need?
The answers to these key questions lie in understanding the behaviour of different sets of users on the platform. Every customer has got his/her needs, interests and limitations. One should always strive to understand these needs and limitations to provide a seamless and personalised experience to its users.
Typically, one can define a few variables for all the customers to understand the customer profile.
- Discount Seeker - Customers who have mostly shopped in sales and have purchased products that were on heavy discounts
- Brand Affinity - For a multi-brand platform, each customer has a little or significant inclination toward a brand. This inclination or preference of a customer is called brand affinity.
- Sweet price point – For every category or type of product, the customer has a set budget on price. One should understand this price nuance while making its platform personalised for the users.
- Distinct Categories - For a multi category platform, whether the customer has bought all the categories or how many of total categories the customer has made purchased in
- Repeat Frequency - After how many days the customer comes back to the platform
After analysing these customer profiles through customer analysis, one can target its customers aptly and provide them exactly what they are looking for.
All of the marketing activities can bring the user to the platform but can not influence him/her to make a purchase. This is a major difference between in-store shopping and online shopping. Physical stores have sales executives which can help customers to find the right product hence influencing the customer’s buying decision. Online stores lack humans as sales executives, but it has its own set of upsides. To aid users to find what they want and eventually convert one may apply some personalised recommendations on the platform. Having personalisation on the platform benefits e-commerce companies in various ways
- Generally personalised results have a higher potential to make the customer purchase. This increases the platform conversion.
- Personalised results can also be used to upsell and cross-sell at the time of checkout or on product pages
- Retargeting campaigns can be designed by using personalised products, and customers can be brought back to the platform
Conclusion: Use Customer Analytics to Speed up Your Growth
Understanding customers’ behaviour and needs help to boost the overall performance of the company. Leveraging customer analytics, which is a subset of data analytics can help us to serve our customers better. Data analytics and usage of CRM helps to understand the buying pattern of every customer. And helps enterprises to plan marketing strategies. There are many analytics consulting firms that have expertise in this field and have developed analytics software also which are created especially for e-commerce customer analytics. Partnering with such a firm is always a wise decision for the management of an e-commerce company. Businesses applying data analytics and CRM have often seen a huge jump in the overall revenue within few years.
Saras, with its effective data management and analytics team, helps Brands across the globe to make informed data-driven decisions to accelerate growth.
Use Customer Analytics to enhance your Business Strategies