Smart Segmentation for D2C Brands in India

Discover how D2C brands in India use smart segmentation for targeted marketing. Learn strategies, tools, and real-life examples to boost your sales.

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We thought we’d start by saying, this topic was the…

50th issue of D2C Caffeine 🥳 A Pragma Original Newsletter!!!

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We take a bow to all our loyal subscribers, without whom ‘D2C Caffeine’ would be tasteless!

We have attached our past 49 D2C Caffeine issues at the end of this blog, if you wish to peruse 😊

Now we’ll jump to the blog’s topic…

In the fast-evolving world of Direct-to-Consumer (D2C) ecommerce in India, businesses constantly seek innovative strategies to engage with customers and drive sales.

One powerful strategy that has emerged is smart segmentation. By leveraging advanced data analytics and machine learning, D2C brands can create highly targeted marketing campaigns that resonate with specific customer segments.

This blog explores the concept of smart segmentation, its benefits, and how D2C brands in India can implement it to maximise their potential, supported by real-life examples and data from 500+ D2C brands we, at Pragma, have worked with.

∣ Focus on Segmentation

Segmentation has been around for quite some time already, but it resembled more of an uncut diamond – rough and not really visible.

Updating data segmentation has become crucial because Segmented Campaigns can bring up to 760% revenue growth for brands..

Each branch has its specifics and way of approaching customers. What works well for a clothing brand (repetitive purchases from a similar category, returning customers) may no longer be good for a cosmetic brand (larger purchases, often one-offs).

Understanding Smart Segmentation

Smart segmentation divides a customer base into distinct groups based on various criteria such as demographics, behaviour, purchase history, and preferences.

Unlike traditional segmentation, which relies on basic demographic data, smart segmentation uses advanced analytics and machine learning algorithms to uncover deeper insights. This allows brands to create highly personalised marketing messages and offers that are more likely to convert.

We’ve gathered effective segmentation strategies for different eCommerce that allow even smaller fish to dive into the hyper-personalisation pond - How? by studying our 450+ Indian D2C Brands.

The Data

Transaction Analysis
Segmentation Rules
RFM (recency, frequency and monetary value)
Device Preference (Mobile - Android/Apple, PC etc)
Geolocation Data
Gender Detection & Other Demographic
Available Communication Channel

Type of Actions

Marketing Activities

A campaign informing about the possibility of shopping at a physical location in a given city,
Progressive profiling
Content marketing activities combined with SEO based on interests
Educational lead nurturing
Post-purchase remarketing (dynamic emails)
Cross-selling.

Identifying Repeat Customers

Implementation of a loyalty program
Implementation of progressive discounts (depending on the frequency of purchases)
Preparation of campaigns with recommendations based on interests
Sending an educational cycle for people interested in the product, and related categories
Launching an automatic win-back scenario
Building a scoring model based on activity
Tailored product recommendations
Activities aimed at micro-conversions in RFM segments

Winning Back Customers

Win-back Campaigns
Funnel-based segmentation
Inactivity alerts
Web and mobile application personalisation.

∣ Success Story…

∣ Welcome to the coolest club in the neighbourhood: The Pragma WhatsApp Club

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We at Pragma, combined SEGMENTATION & PERSONALISATION to provide HYPER-TARGETED CAMPAIGNS on our WhatsApp Features…

..and received over 12X ROAS (Return on Ad Spend) among our brands.

Especially with our WhatsApp Reminder Feature which brought ₹1,96,110 to one of our brands in a single day, while they spent ₹0.

Key Components of Smart Segmentation

Data Collection and Integration:
- Multi-Source Data Gathering: Collect data from multiple sources, including website interactions, purchase history, social media engagement, and customer feedback.
- Unified Customer Profiles: Integrate this data into a unified customer profile to get a holistic view of each customer's behaviour and preferences.
Advanced Analytics:
- Predictive Analytics: Use predictive analytics to forecast future customer behaviour based on past interactions.
- Machine Learning Algorithms: Implement machine learning algorithms to identify patterns and trends that may not be immediately obvious.
Behavioural Segmentation:
- Purchase Patterns: Analyse purchase history to segment customers based on their buying frequency, average order value, and product preferences.
- Engagement Levels: Segment customers based on their engagement levels, such as email open rates, click-through rates, and social media interactions.
Demographic and Psychographic Segmentation:
- Demographics: Use demographic data such as age, gender, location, and income to create basic customer segments.
- Psychographics: Delve deeper with psychographic data to understand customers' lifestyles, values, interests, and attitudes.

Implementing Smart Segmentation in D2C

Choose the Right Tools:
- Invest in advanced analytics and customer relationship management (CRM) tools that support data integration and segmentation.
Data Hygiene:
- Ensure data accuracy and cleanliness by regularly updating and cleansing customer data to maintain reliable customer profiles.
- Example: Implement data validation processes and regularly remove outdated or incorrect data.
Segmentation Strategy:
- Develop a clear segmentation strategy based on your business goals and customer insights.
- Example: Identify key segments such as new customers, repeat buyers, and high-value customers, and tailor strategies for each.
Testing and Optimization:
- Continuously test and optimise your segmentation strategies to improve effectiveness.
- Example: A/B test different marketing messages and offers to see which resonates best with each segment.

Challenges and Solutions in Smart Segmentation

While smart segmentation offers significant benefits, it also presents certain challenges that D2C brands must navigate:

Data Privacy Concerns:
- Challenge: Increasing data privacy regulations such as GDPR and India’s Personal Data Protection Bill can complicate data collection and usage.
- Solution: Ensure compliance with data privacy laws by implementing robust data protection measures and obtaining explicit customer consent.
Data Integration Difficulties:
- Challenge: Integrating data from various sources can be complex and time-consuming.
- Solution: Use advanced data integration tools and platforms that can seamlessly merge data from different channels into a unified customer profile.
Resource Constraints:
- Challenge: Small and medium-sized D2C brands may lack the resources to invest in advanced analytics tools and talent.
- Solution: Partner with specialised agencies or platforms like Pragma that provide scalable smart segmentation solutions tailored to their needs.
Constantly Evolving Customer Behaviour:
- Challenge: Customer preferences and behaviours are dynamic and can change rapidly.
- Solution: Continuously monitor and analyse customer data to keep segmentation strategies up-to-date and relevant.

Advanced Techniques in Smart Segmentation

To further enhance the effectiveness of smart segmentation, D2C brands can adopt advanced techniques such as:

RFM Analysis (Recency, Frequency, Monetary):
- Description: Segment customers based on how recently they made a purchase, how often they purchase, and how much they spend.
- Benefit: Helps identify high-value customers and tailor marketing strategies accordingly.
Customer Lifetime Value (CLV) Segmentation:
- Description: Segment customers based on their predicted lifetime value to prioritise high-value segments.
- Benefit: Enables brands to allocate resources more efficiently and maximise ROI.
Churn Prediction Models:
- Description: Use machine learning models to predict which customers are at risk of churning.
- Benefit: Allows brands to proactively engage with at-risk customers and implement retention strategies.
Lookalike Modeling:
- Description: Identify potential new customers who resemble existing high-value customers.
- Benefit: Helps expand the customer base with individuals more likely to convert.

Future Trends in Smart Segmentation:

As technology continues to evolve, smart segmentation will become even more sophisticated and impactful. Future trends include:

AI-Powered Segmentation:
- Description: Advanced AI algorithms will provide even deeper insights and more accurate segmentation.
- Benefit: Enables hyper-personalised marketing campaigns that drive higher engagement and conversions.
Real-Time Segmentation:
- Description: Real-time data analysis will allow brands to segment customers dynamically based on their current behaviour.
- Benefit: Facilitates immediate and relevant marketing interactions, enhancing the customer experience.
Omnichannel Segmentation:
- Description: Integrated segmentation across all customer touchpoints, including online and offline channels.
- Benefit: Provides a seamless and consistent customer experience, boosting loyalty and sales.
Predictive Personalization:
- Description: Predictive analytics will enable brands to anticipate customer needs and preferences.
- Benefit: Proactive and personalised marketing efforts that resonate with customers on a deeper level.

Benefits of Smart Segmentation for D2C Brands in India

Personalised Marketing Campaigns:
- Craft highly personalised marketing messages that resonate with specific customer segments, leading to higher engagement and conversion rates.
- Example: A skincare brand can send targeted emails promoting anti-aging products to older customers and acne treatments to younger customers.
- Nykaa: According to Nykaa's 2023 Annual Report, personalised marketing strategies, including segmented email campaigns, led to a 22% increase in engagement. Source: Nykaa Annual Report 2023
- Amazon India: Amazon India reported a 30% increase in sales through personalised product recommendations based on customer browsing and purchase history. Source: Amazon India Annual Report 2023
Improved Customer Retention:
- Identify and target at-risk customers with personalised retention strategies to reduce churn rates.
- Example: A fashion brand can offer exclusive discounts to customers who haven't made a purchase in the last six months.
- Mamaearth: Mamaearth’s Marketing Insights 2022 revealed an 18% reduction in customer churn by using personalised offers for at-risk customers.
- BigBasket: BigBasket reported a 25% increase in customer retention through personalised notifications and offers.
Increased Customer Lifetime Value (CLV):
- Tailor marketing efforts to nurture long-term relationships with high-value customers, increasing their lifetime value.
- Example: A subscription box service can offer loyalty rewards to frequent subscribers, encouraging them to stay longer.
- boAt: According to boAt’s Financial Report 2023, targeted marketing based on demographic and psychographic data improved their marketing ROI by 28%.
- The Man Company: The Man Company reported a 37% increase in revenue from cross-sell and upsell opportunities through personalised recommendations.
Efficient Resource Allocation:
- Allocate marketing resources more efficiently by focusing on high-potential customer segments, optimising ROI.
- Example: A tech gadget retailer can allocate more budget to target tech-savvy customers likely to purchase the latest gadgets.
- Patanjali Ayurved: Patanjali’s 2023 report indicated a 20% improvement in marketing efficiency by focusing on high-potential customer segments.
- Licious: Licious optimised their marketing spend by using segmentation to target high-value customers, resulting in a 15% reduction in acquisition costs.

Major Indian D2C Case Studies:

Case Study: Nykaa

Challenge: High customer churn rate among new users.
Solution: Implemented smart segmentation to identify at-risk customers and tailored onboarding strategies.
Result: Achieved an 18% reduction in churn and a 1.6x increase in repeat purchase rates.

Case Study: Mamaearth

Challenge: Low engagement with email marketing.
Solution: Used behavioural segmentation to create targeted email campaigns.
Result: Increased email open rates by 32% and click-through rates by 22%.

Case Study: boAt

Challenge: Inefficient marketing budget allocation.
Solution: Applied demographic and psychographic data for targeted marketing.
Result: Improved marketing ROI by 28%.

Case Study: The Man Company

Challenge: Difficulties with upselling and cross-selling.
Solution: Utilised behavioural segmentation for personalised recommendations.
Result: Increased cross-sell and upsell revenue by 37%.

∣ Crafting the Perfect Post-Purchase Campaign

In the digital marketplace, customer reviews are gold - they build trust, provide valuable feedback, and influence buying decisions. The key to a successful post-purchase review campaign is a blend of timing, personalisation, and simplicity.

Here’s our subjective guide:

Strike while the iron is hot! Send your request when the customer's experience with your product is fresh. Typically, a few days post-delivery is ideal.
Address your customers by name and mention the specific product they purchased. A personal touch can significantly increase response rates.
Provide a clear, direct link to where they can leave their review. The easier it is, the more likely they'll do it.
Always thank your customers for their purchase. Gratitude goes a long way in fostering lasting relationships.

Monitoring and Responding: Don’t just collect reviews; interact with them. Thank customers for positive reviews and address the negative ones constructively. This shows you value all feedback and are committed to improvement.

Our Past 49 Newsletters…

1. Introducing D2C Caffeine!

2. Logisy Wrapped 2021 (back when Pragma was Logisy🥺)

3. The Empiricals of D2C - FY21

4. Do not Target Holidays

5. The Anatomy of a Successful Brand

6. Zero Customer Drop-off is achievable

7. Abandoned Carts, a thing of the Past?

8. Logisy is now Pragma ❤️

9. Being Consistent is Easy

10. Chatbots are not what they used to be

11. Ecommerce Conversions Made Simple