Among multiple other lifestyle changes, COVID-19 has also altered customers’ shopping habits. From being ‘forced’ to shop online to finding it comfortable – customers now engage with brands on their terms and expect a personalized and a meaningful experience. With the third-largest online shopper base of 150 million in FY21 globally, the Indian e-commerce market is expected to grow to US$ 200 billion by 2026.
What does it mean for the retail industry?
Back in 2020, Forrester predicted that organizations need to leverage customer insights and quantify the business impact of customer experience (CX) initiatives to stay in business. As traditional retailers move to e-commerce, winning and retaining customers has become expensive. Therefore, it has become imperative to follow, engage, and understand the customer across their journeys.
Importance of 360-degree view of customer
Research reveals that drawing on customer-related metrics and interlinking them intelligently can increase EBITDA (a measure of operating profit) by 15 to 25 percent. However only 14% of organizations have a 360-degree view of the customer, which is necessary for micro-segmentation and targeting, dynamic marketing campaigns, proactive error resolution, and contextualized customer service in real-time.
With the retail analytics market projected to reach US$23.8 billion by 2027[3], it’s a no-brainer that data analytics plays a huge role in customer acquisition and retention. While data analytics has multiple advantages, some of them are as follows:
Customer acquisition
Customer data analytics give an overall picture of what a business’s customers look and act like, which can help with targeted customer acquisition efforts. By leveraging data science models, companies can strategize cross-channel marketing to target prospective customers and maximize return on campaigns. Apart from this, if you’re looking to increase customer reach, data analytics can help you by tapping preferences and purchase patterns such as demographics, affinity, in-market, remarketing, etc.
You can also automate and optimize data feed updates, create dd groups to target specific products, manage campaigns like thematic search, retargeting strategy, and implementation, ad extensions more effectively using data analytics for acquiring new customers. Aligning bidding strategy with KPIs, improving quality score on Google, increasing online visibility by enhancing local search results and optimizing user experience, optimizing marketing strategies and improving the effectiveness of advertising by selecting the suitable attribution model are some other ways in which data analytics can help you with customer acquisition.
Customer retention
According to Bain & Company, increasing customer retention rates by 5% can increase profits from 25% to 95%. Customer retention analytics can help businesses to calculate the lifetime value of customers by leveraging RFM (Recency, Frequency & Monetary) Framework to provide for acquisition and retention costs. It can also develop churn prediction models by using static and customer engagement variables, select the optimal attribution model to optimize marketing strategies and improve the effectiveness of advertising.
Personalize customer experience
Data analytics can help segment customers based on shared characteristics and build detailed profiles for individual customers to enable retailers to deliver hyper-personalized product recommendations, marketing campaigns, product discounts, etc. You can also identify disengaged customers, potential long-term customers, and frequent buyers to strategize offers and incentives.
To sum it up…
While all businesses want to enhance customer experience, limit attrition, and increase their base, some do better than others. A few tips mentioned below to help you get the most out of data analytics:
Take an integrated approach: Use analytics to develop an integrated roadmap for growth instead of using it in siloes.
Map potential customers with existing ones: Customers are less likely to churn if they are like your primary target customers. Apply algorithms to compare the features and characteristics of your existing customers with those of your potential customers.
Use predictive analytics: By looking at historical data, use machine learning to predict what your customers will like or dislike.
Author:
Anuj Gupta, Co-Founder, Eucloid
The post Role of Data Analytics in Amplifying Customer Acquisition and Retention Rates appeared first on Analytics Insight.
Among multiple other lifestyle changes, COVID-19 has also altered customers’ shopping habits. From being ‘forced’ to shop online to finding it comfortable – customers now engage with brands on their terms and expect a personalized and a meaningful experience. With the third-largest online shopper base of 150 million in FY21 globally, the Indian e-commerce market is expected to grow to US$ 200 billion by 2026.
What does it mean for the retail industry?
Back in 2020, Forrester predicted that organizations need to leverage customer insights and quantify the business impact of customer experience (CX) initiatives to stay in business. As traditional retailers move to e-commerce, winning and retaining customers has become expensive. Therefore, it has become imperative to follow, engage, and understand the customer across their journeys.
Importance of 360-degree view of customer
Research reveals that drawing on customer-related metrics and interlinking them intelligently can increase EBITDA (a measure of operating profit) by 15 to 25 percent. However only 14% of organizations have a 360-degree view of the customer, which is necessary for micro-segmentation and targeting, dynamic marketing campaigns, proactive error resolution, and contextualized customer service in real-time.
With the retail analytics market projected to reach US$23.8 billion by 2027[3], it’s a no-brainer that data analytics plays a huge role in customer acquisition and retention. While data analytics has multiple advantages, some of them are as follows:
Customer acquisition
Customer data analytics give an overall picture of what a business’s customers look and act like, which can help with targeted customer acquisition efforts. By leveraging data science models, companies can strategize cross-channel marketing to target prospective customers and maximize return on campaigns. Apart from this, if you’re looking to increase customer reach, data analytics can help you by tapping preferences and purchase patterns such as demographics, affinity, in-market, remarketing, etc.
You can also automate and optimize data feed updates, create dd groups to target specific products, manage campaigns like thematic search, retargeting strategy, and implementation, ad extensions more effectively using data analytics for acquiring new customers. Aligning bidding strategy with KPIs, improving quality score on Google, increasing online visibility by enhancing local search results and optimizing user experience, optimizing marketing strategies and improving the effectiveness of advertising by selecting the suitable attribution model are some other ways in which data analytics can help you with customer acquisition.
Customer retention
According to Bain & Company, increasing customer retention rates by 5% can increase profits from 25% to 95%. Customer retention analytics can help businesses to calculate the lifetime value of customers by leveraging RFM (Recency, Frequency & Monetary) Framework to provide for acquisition and retention costs. It can also develop churn prediction models by using static and customer engagement variables, select the optimal attribution model to optimize marketing strategies and improve the effectiveness of advertising.
Personalize customer experience
Data analytics can help segment customers based on shared characteristics and build detailed profiles for individual customers to enable retailers to deliver hyper-personalized product recommendations, marketing campaigns, product discounts, etc. You can also identify disengaged customers, potential long-term customers, and frequent buyers to strategize offers and incentives.
To sum it up…
While all businesses want to enhance customer experience, limit attrition, and increase their base, some do better than others. A few tips mentioned below to help you get the most out of data analytics:
Take an integrated approach: Use analytics to develop an integrated roadmap for growth instead of using it in siloes.
Map potential customers with existing ones: Customers are less likely to churn if they are like your primary target customers. Apply algorithms to compare the features and characteristics of your existing customers with those of your potential customers.
Use predictive analytics: By looking at historical data, use machine learning to predict what your customers will like or dislike.
Author:
Anuj Gupta, Co-Founder, Eucloid
The post Role of Data Analytics in Amplifying Customer Acquisition and Retention Rates appeared first on Analytics Insight.