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Consumers today are more openly incorporating retail brands into their daily lives that serve a specific purpose or deliver on expectations. On the other hand, the retail business space constantly evolves and faces challenges like supply chain disruption, digital disruption, changing market conditions, customer expectations, data infrastructure, etc. Traditional marketing approaches in retail are not as practical as they once were, and brands are actively adopting modern digital solutions to stay competitive, reduce strategic and technological ambiguity, and improve consumer experience and profitability.

Personalized Customer Experiences

Personalization is a key focus area for retailers to establish a long-term competitive advantage. It involves delivering multi-touch, unique and tailored customer interactions based on the information like buyer’s intent, behavioural cues, historical data, and other attributes like demographics, interests, and preferences. Apparel apps that remember the clothing size, wish lists, commonly used filters and suggest products based on past purchases are a minimal use-case.

Retailers today require powerful and contextual intelligence platforms to understand shopper intent, preferences and what they expect from brand or website interactions. And leveraging AI and automation is quintessential to delivering those relevant and actionable insights that enhance the customers’ shopping journey at scale.

A successful personalization should delight the customers with a unique experience and emotionally connect them with the brand.


Benefits of Retail Personalization


  • Higher Customer Satisfaction & Retention
  • Instant Brand Recognition
  • Higher Emotional Connect and Engagement
  • Improved Campaign ROI / Conversion
  • Improved Customer Lifetime Value

Hyper-Localization is not just a hype

Retail Localization is customizing the business approach to meet the demands of defined customer and market segments, with more local/regional demand context. Retailers widely implement traditional localization strategies by having the right product mix to meet the geographic, religious, cultural, linguistic and lifestyle preferences, and that’s good but not enough. They need to leverage Hyper Localization – Localization for the consumers of the digital era.

Hyper Localization is a big data and analytics-driven effort that adds value to traditional Localization. It is one of the ideal ways to deliver a well-targeted, personalized shopping experience for the customers.

Here are a few hyper-localization initiatives that retailers can start with:

  • Facilitating in-store customer touchpoint kiosks with localized themes and offerings to assist them
  • Creating E-retail websites/apps with multilingual and multi-currency options
  • Producing localized digital content in various formats across different channels
  • Implementing personalized content marketing efforts that attract specific customers and market segments
  • Performing Local SEO strategies with localized content to gain market visibility organically
  • Running Geolocation ad campaigns for local and regional keywords that have business potential
  • Driving seasonal marketing campaigns to drive sales by taking advantage of local events
  • Providing personalized recommendations to the customers based on regional preferences
  • Providing last-mile fulfilment for customer convenience and improved service experience

Well strategized hyper-localization efforts will amplify brand visibility and customer loyalty, eventually increasing store footfalls. However, it requires immense data research and analysis to be successful, making it predestined for retailers to have advanced AI and data infrastructure support.

Drive Performance with Data

Retailers have been putting data into action to drive their business operations efficiently, and there is still more potential. A comprehensive data-driven approach can enable retailers to achieve stellar customer experience, operational efficiency, cost savings, and portfolio development. It is crucial to build a data-driven culture focused on accessibility & intelligence, and strengthen analytics across different business functional units.

Here are some significant retail analytics practices:

Strategic Pricing Decision:

  Product price fixing based on customer feedback, competitive and marketing intelligence insights, instead of the traditional pricing approach.

Product Display & Assortment Optimization:

Applying data analysis for optimal product placement that maximizes profit and providing suitable product-mix offerings in demand by analyzing consumer behaviour.

Data-Driven Site Selection:

 Leveraging location intelligence for strategic site selection for ordinary stores and BOPIS. (Buy Online, Pick Up In-Store)

Supply Chain Movement:

 Analyzing various business information to predict demand and manage the supply chain accordingly. It also helps in managing resources and distribution.

Relevant Customer Experiences:

 Extracting insights from tracking and analyzing shopper behavior, identity & data to understand their needs better, personalize communication, improve the customer journey and build loyalty.

Understanding real-time and historical sales, inventory, operational and customer data helps retailers take the right business decisions. A solid data analytics ecosystem can bring incredible benefits to every retail business out there – right from finding anomalies and opportunities to automating and personalizing marketing approaches.

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