D2C Brands → Data ← Consumers

hether you're looking to boost sales, improve customer engagement, or drive long-term growth, data collection is a crucial component of any successful D2C marketing plan. Discover why data matters and how it can help your brand succeed today!

Data is directly proportional to ‘Retention

Because with the right information, optimisation can soon follow, and then comes increased consumer satisfaction..

6 reasons why Data and Data Collection is crucial for D2C Brands in India

  1. Better understanding of customers: This can help brands better understand their customers and create products and services that meet their needs and preferences.
  2. Optimising the Sales Funnel: Data can be used to track and optimise the entire customer journey, from initial brand discovery to purchase and beyond. By analysing customer behaviour at each stage, D2C brands can improve their sales funnel, resulting in higher conversion rates and increased revenue.
  3. Inventory Management: Data can be used to forecast demand, track inventory levels, and optimise pricing strategies. This allows D2C brands to reduce inventory costs and minimise waste, while still meeting customer demand.
  4. Improving the customer experience: Collecting data about how customers interact with a brand's products and services, brands can identify areas for improvement and make changes to enhance the customer experience.
    This can include things like streamlining the checkout process, improving the functionality of a website or app, or providing better customer service.
  5. Analysing Competitors: Data can also be used to analyse competitor activity, understand their strengths and weaknesses, and identify opportunities for growth. This helps D2C brands develop strategies to stand out in a crowded marketplace and gain a competitive advantage.
  6. Scaling the Business: Finally, data allows D2C brands to scale their business more efficiently. By analysing customer behaviour and sales data, brands can identify which marketing channels and products are most effective and allocate resources accordingly. This helps to optimise growth while minimising costs.

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That’s just the gist of why Data is quintessential.

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Data Collection comes next, which can be split into stages/criteria

  1. Conversion Funnel
  2. Geography, and
  3. Individual (the consumer)
  4. Fulfilment/Last-mile services

NOTE: Before we get into it, FYI, Pragma compiles the information of them all - from 450+ brands. Meaning, we optimise every individual D2C Brand by studying 450+ others!

1) Conversion Funnel

Understanding which stage of the funnel a potential customer/lead is at, the brand can optimise strategy for campaigns, updates, advertising channels etc.

1. Education & Awareness stage

2. Interest and Consideration stage

3. Action stage - Transition or conversion

Based on which you can selectively highlight:

Product information: This includes details such as the price, features, and specifications of the product.

Customer reviews: Reading reviews from other customers can help you get a sense of the product's quality and whether it meets the needs of other people who have purchased it.

Comparison shopping: Comparing the price and features of similar products from different sellers can help you make an informed decision about which product to purchase.

Availability: It's important to know if a product is in stock or if there will be a delay in shipping.

And more.

How to gather the required Data?

Surveys: Surveys can be used to gather data on the target audience's knowledge, understanding, and interest in the brand and its products.

By asking questions about the brand's product features and more, an ecommerce business can identify areas where customers may be confused or disengaged and develop strategies to educate and engage them.


Website Analytics: Website analytics can provide insight into the target audience's knowledge, understanding, and interest in the brand and its products. 


By analysing metrics such as bounce rates, time on site, and pages per session, a brand can identify areas where customers may be confused or disengaged and develop strategies to optimise the user experience and thereby increase engagement.


Social Media Monitoring: Social media monitoring can help an ecommerce business to understand the target audience's perception of the brand and its products and identify which types of content and promotions are generating the most interest and engagement. 


By developing targeted social media campaigns that address customer concerns and questions, an ecommerce business will inevitably increase customer engagement and drive sales.


Customer Feedback: Collecting feedback from customers who are in the consideration stage can provide valuable insights into the factors that influence their purchasing decisions. 


By analysing this data, a brand can identify common concerns or questions and develop strategies to address them through targeted marketing and educational initiatives.



2) Geography


Understanding sales based on the city/state/country is crucial to know…

  • What product sells where
  • Which area has most returns, cancelation and more
  • Where do you spend most in terms of logistics etc

With a brand’s internal data along with Pragma’s 450+ brands - one can find new opportunities i.e. new regions that can be targeted.

And these factors help brands understand

  1. Which carrier partner is most suitable for them
  2. Are there any cheaper/viable logistic services available
  3. Would multiple carrier partners be a better choice
  4. What inventories could be shutdown or optimised
  5. Where similar audience base reside etc


Here are some ways D2C brands in India can use geography data:

Targeted Marketing: By analysing geography data, D2C brands can identify which regions have the highest concentration of potential customers and develop targeted marketing campaigns to reach those audiences. 

For example, a brand may choose to focus its marketing efforts on regions with high population densities or a large number of customers who have previously engaged with the brand.

Regional Product Offerings: D2C brands can use geography data to understand the unique needs and preferences of different regions and tailor their product offerings accordingly. 

For example, a brand may offer regional variations of products or services that cater to the specific cultural and dietary preferences of different regions.

Personalised Experiences: By collecting and analysing data on customer location, D2C brands can offer personalised experiences to customers based on their geographical location. This can include personalised marketing messages, targeted promotions, and customised product recommendations that are tailored to the customer's region.

For example, customers living in hot and humid regions could be recommended products that are more suitable for oily skin, while customers in colder regions could be recommended products that provide more hydration.

Localised Fulfilment: D2C brands can use geography data to optimise their supply chain and fulfilment operations. By understanding which regions have the highest demand for their products, brands can optimise their inventory management and ensure that products are delivered to customers in a timely and cost-effective manner.

For example, a D2C brand that sells perishable food items could set up regional distribution centres to ensure that the products are delivered to customers in a timely and fresh manner. This would reduce the transportation time and costs, and also improve the customer experience by providing them with fresher products.


3) Individual (the consumer)

Understand the individual and personalise!

a) Communication Data

  • Offer real time communication on orders. Connecting the consumer to the brand and the carrier partner, avoiding RTO/NDR
  • Run A/B testing campaigns on different audience segments, to hyper personalise further
  • Improve purchase forecasting with demography, geography, and other data

b) Behavioural Data

  • Purchase History: Information on the items purchased by the customer, the frequency of purchases, and the average order value.
  • Product usage data: Keeping track of how you use the product can help you get the most out of it and identify any potential problems or issues.
  • Customer feedback: Providing feedback about your experience with the product and the seller can help improve the overall customer experience
  • Web analytics: By tracking and analysing data about how customers interact with an e-commerce website, companies can identify patterns and trends that can help them optimise the site for a better customer experience. 

c) Cross platform Data

  • Demographics: Information on the age, gender, location, and other demographic characteristics of the customer.
  • Social Media Activity: Information on the customer's social media activity, including likes, shares, and comments on products, which can help ecommerce businesses understand customer sentiment and engagement.
  • Customer service data: Data collected through customer service channels, such as social media, email, and chat, can provide valuable insights into customer needs and concerns.
  • Trigger cross-selling sales plays with help of intelligent product recommendations on the final most parts of the customer journey like shopping cart, order summary pages, etc.

4) Fulfilment/Last-mile services

Collecting data can help ecommerce companies in India improve their last-mile delivery services, which is the final step of the delivery process that brings the product from the local distribution centre to the customer's doorstep. 

Key areas ‘Fulfilment Data’ plays an important role:

Delivery Route Optimization: By collecting data on traffic patterns, road conditions, and delivery addresses, ecommerce companies can optimise their delivery routes to reduce delivery time and transportation costs.

Real-Time Tracking: Ecommerce companies can collect data on the location of delivery vehicles in real-time, allowing customers to track their deliveries and receive updates on delivery status. This improves customer satisfaction and reduces the likelihood of missed deliveries.

Predictive Analytics: By analysing historical data on delivery patterns and customer behaviour, ecommerce companies can predict demand and optimise their delivery operations accordingly. This can include adjusting delivery schedules, allocating resources, and optimising inventory management.

Customer Feedback: Collecting customer feedback can help ecommerce companies identify pain points in the delivery process and make improvements accordingly. This includes feedback on delivery time, delivery personnel, and overall customer experience.

Automated Processes: By automating certain aspects of the delivery process, such as dispatching orders or scheduling deliveries, ecommerce companies can streamline their operations and reduce the risk of errors.

To Wrap it Up

D2C Brands → Data ← Consumers

Data is the key that bridges the gap between D2C Brands and their Online Consumers.

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