D2C’s lack of Post-Purchase Visibility

D2C's post-purchase visibility challenges & solutions.

If your Post Purchase Visibility SUCKS…

So will your RETENTION!

‍Meaning, a clear view of a brand's intricate operational structure is essential to ensure the smooth functioning of supply chains and customer satisfaction that helps in solving the problem of: D2C’s lack of Post-Purchase Visibility.

Going Beyond Sales: Why D2C Must Prioritise Post-Purchase Experience

And Data transparency or Data Visibility plays a crucial role in enhancing the resilience of brands. 

‍Data visibility pertains to the seamless accessibility for you to monitor, present, and analyse data derived from diverse sources across the customer journey - mainly post purchase, because that’s where lies the key to retention.


What Makes The D2C Customer Tick?

For D2C brands to really make customer satisfaction a priority, they need to walk a mile in their customer's shoes. This means understanding every step of the customer's experience, from the moment they start browsing the website to after they've bought something and need help. 

At each point along the way, the brand needs to make sure it's meeting the customer's needs, wants, and expectations.

The “Data to focus” on comes from 4:

  1. Customer Relationship Management (CRM)
  2. Inventory Management
  3. Returns Management, and 
  4. Logistics Management

Technology Trends To Help You Grow Your D2C Business

Customer Engagement Metrics:
Monitor metrics such as email open rates, click-through rates, website engagement, and social media interactions. These metrics help evaluate the effectiveness of your post-purchase communication and engagement strategies.

Product Performance:
Analyse data related to individual product performance, including sales volumes, customer reviews, and returns.
This information can help identify popular products, assess the need for product improvements, and inform inventory management decisions.

Customer Feedback: 

  • Because 90% of consumers read online reviews before making a purchase decision.
  • 86% of consumers hesitate to purchase from a business with negative online reviews. 
  • Companies that actively gather and utilise customer feedback outperform competitors by 58%.

Checkout Data:

Customer Demographics:
Because collecting demographic data such as age, gender, location, and occupation to gain insights into your customer base is the key to targeted marketing campaigns, product customisation, and understanding your customer segments.

Purchase History: 

  • Because analysing purchase behaviour can help identify cross-selling and upselling opportunities, leading to increased revenue. 
  • 49% of consumers have made impulse purchases after receiving personalised recommendations.
  • Repeat customers generate 40% of a brand's revenue, despite making up only 8% of its customer base.

Customer Support Interactions:
Keep a record of customer interactions with your support team, including queries, complaints, and resolutions. Analysing this data can help identify common pain points, improve support processes, and enhance customer satisfaction.

Customer Lifetime Value (CLV):
Calculate the CLV, which is the predicted net profit attributed to a customer over their entire relationship with your brand.

By understanding the CLV, you can determine the profitability of different customer segments and allocate resources accordingly.

  • Repeat customers have a 60-70% chance of converting, while new customers have a 5-20% chance.
  • Acquiring a new customer is 5-25 times more expensive than retaining an existing one. 

Customer Segmentation:
Segment customers based on various criteria such as purchase behaviour, preferences, or demographics.

This segmentation can help tailor marketing campaigns, personalise communications, and create targeted offers for different customer groups.

Return and Refund Data: 

  • Because a seamless return process can increase customer loyalty, with 92% of consumers likely to buy again from a retailer with an easy return policy.
  • 67% of consumers check the return policy before making a purchase.
  • 58% of consumers expect a hassle-free return process.

Average Order Value (AOV):
Calculate the AOV to understand the average amount customers spend on each transaction.
Analysing AOV can help identify opportunities to increase sales through strategies like cross-selling, upselling, or offering bundle deals.

Mobile Usage Data:
If you have a mobile app, track user behaviour within the app, such as time spent, features used, and purchase patterns.
This data can provide insights into mobile app engagement and help optimise the app experience.

Social Media Mentions Etc:
Monitor social media platforms for mentions of your brand, products, or customer experiences.
Analysing social media conversations can provide valuable insights into brand sentiment, user-generated content, and potential influencers or brand ambassadors.

  • 88% of consumers trust online reviews as much as personal recommendations. 
  • User-generated content has a 4.5% higher conversion rate compared to non-user-generated content.
  • 74% of consumers rely on social media to guide their purchasing decisions. 

Referral Data:
Keep track of customer referrals and the resulting conversions. This data helps evaluate the effectiveness of referral programs and identify customers who act as brand advocates.

Customer Satisfaction & Net Promoter Score (NPS):
Implement customer satisfaction surveys or metrics like Customer Satisfaction Score (CSAT) or Customer Effort Score (CES).
These metrics help gauge overall satisfaction levels and identify areas where improvements can be made.

  1. Because a 5% increase in customer retention can lead to a 25%-95% increase in profits. 
  2. Customers with a high NPS score spend, on average, 2.6 times more than customers with low scores. 
  3. 84% of customers consider customer service as a key factor in their decision to purchase from a brand. 

Channel Performance:
Track and analyse the performance of different sales channels, such as your website, mobile app, marketplace platforms, or social media storefronts. This data can help identify the most effective channels for sales and customer acquisition.

Customer Retention Rate:
Measure the percentage of customers who make repeat purchases over a specific period. Monitoring customer retention helps assess the effectiveness of your post-purchase strategies and the level of customer loyalty.

Abandoned Cart Data:
Track instances where customers add products to their cart but do not complete the purchase. Analysing this data can help identify potential barriers or issues in the checkout process and optimise it to improve conversion rates.

Social Proof Metrics:
Monitor and analyse social proof metrics such as customer reviews, ratings, testimonials, and social media mentions. This data can provide insights into customer sentiment, brand reputation, and help identify areas for improvement.

Customer Journey Analytics:
Analyse the customer journey from initial website visit to post-purchase interactions. This data can help identify bottlenecks or areas where customers drop off, allowing you to optimise the user experience and increase conversion rates.

Benefits of Post-purchase Data Visibility?

Benefits of Post-purchase Data Visibility?

  1. Enhanced Customer Understanding:

    Post-purchase data visibility enables brands to gain deeper insights into customer behaviour, preferences, and satisfaction levels. By analysing this data, brands can understand customer needs, preferences, and purchase patterns, allowing for better personalisation and targeted marketing efforts.
  2. Improved Customer Experience:

    With post-purchase data visibility, brands can track and monitor the entire customer journey, from initial purchase to post-purchase interactions. This visibility helps identify pain points, optimise processes, and provide proactive customer support, leading to an improved overall customer experience.
  3. Effective Personalisation:

    Access to post-purchase data allows brands to personalise their interactions and offerings to individual customers. By understanding customer preferences and purchase history, brands can deliver tailored recommendations, personalised promotions, and relevant content, increasing customer engagement and satisfaction.
  4. Targeted Marketing Campaigns:

    Post-purchase data visibility enables brands to segment their customer base and create targeted marketing campaigns. By analysing customer demographics, purchase behaviour, and preferences, brands can tailor their messaging and offers to specific customer segments, increasing the effectiveness of their marketing efforts.
  5. Improved Inventory Management:

    With visibility into post-purchase data, brands can better manage their inventory and supply chain. By analysing purchase patterns, return rates, and demand fluctuations, brands can optimise stock levels, reduce stockouts, and improve fulfilment efficiency, leading to better customer satisfaction and cost savings.
  6. Proactive Issue Resolution:

    Post-purchase data visibility allows brands to proactively identify and address issues faced by customers. By monitoring customer feedback, reviews, and support interactions, brands can quickly identify and resolve customer concerns, minimising negative impacts and building customer loyalty.
  7. Data-Driven Decision Making:

    Access to post-purchase data provides brands with valuable insights for informed decision making. By analysing data on customer behaviour, satisfaction levels, and trends, brands can make data-driven decisions related to product development, marketing strategies, customer support improvements, and overall business growth.
  8. Customer Retention and Loyalty:

    Leveraging post-purchase data visibility helps brands enhance customer retention and loyalty. By understanding customer preferences, addressing pain points, and providing personalised experiences, brands can foster long-term relationships with customers, leading to increased customer loyalty and repeat purchases.

Overall, post-purchase data visibility empowers D2C brands in the Indian e-commerce market to make informed decisions, optimise operations, and deliver exceptional customer experiences, thereby driving business growth and success.


1. How does the lack of physical stores in D2C impact post-purchase experience in India?

Without stores, D2C brands miss in-person interaction and have to rely solely on digital communication for post-purchase updates and support.

2. How does India's fragmented delivery landscape affect D2C post-purchase visibility?

Multiple delivery partners can make it difficult for D2C brands to track orders efficiently and provide clear post-delivery support.

3. In D2C, how can focusing on customer acquisition over retention hurt post-purchase visibility?

Prioritising new customers might lead to neglecting existing ones, creating a gap in post-purchase communication and feedback collection.

4. Can you give an example of a D2C brand in India that excels in post-purchase communication?

A brand like MyGlamm uses personalised post-purchase emails for product recommendations and tutorials, enhancing customer experience.

5. What's one way D2C brands in India can leverage technology to improve post-purchase visibility?

Implementing CRM (Customer Relationship Management) tools can streamline communication and track customer interactions for better post-purchase support.

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