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Amit Rohatgi

Amit Rohatgi is VP-Product Consulting and leads prospect and customer discussions for Manthan in North America. In this role, he focuses on helping consumer-facing businesses leverage data, advanced analytics, and marketing technologies to drive customer engagement and profits. Amit brings deep expertise on technology products, solutions and industry best practices. His 18+ years of experience in data management, CRM, marketing and analytics in companies such as IBM and Symphony IRI comes in handy in creating value for clients.

The six steps to align marketing to customer journey in retail

Plenty has been said about Journey Marketing and it is at the top of the list while evaluating marketing technology today. Rightly so. In a crowded retail landscape, customers have access to options and information from the comfort of their home, and just one below average touchpoint is enough to lose them. Aligning marketing to the customer journey is no more a luxury. Journey marketing brings a fundamental shift in the way marketers reach out to customers. Marketers use their understanding of the customer, their possible lifecycle stage and purchase paths to create a valuable experience for the customer.

Watch a 2 minute video of how journeys can be configured in Manthan Customer Marketing Platform

  This requires work, but let me demystify the process. Here is a step-by-step approach to define and implement customer journey targeting:

1. Create a customer journey map and identify gaps

This should be the starting point for the marketer. A journey map outlines customer’s interactions and experience with the brand across channels over time. It is obvious that this map should reflect the customer’s point of view – for this, step into the customer’s shoes, and don’t be tainted by the brand’s internal process view. An as-is journey map and an ideal state map should be created. The gap is what journey marketing should help bridge.  

2. Set goals for journey stages

Conversion is what all businesses chase, however, this internal goal needs to be translated to customer expectations. As a customer moves across stages, her need for content and information changes. For example, after she has selected the dress, she is looking for the return policy and shipping information. Brand’s inability to serve contextual content across each stage of the journey will result in losing the sale, and a reduced chance of the customer re-visiting you. Marketers need to define what a customer would expect from each stage, rather than pushing conversions.  

3. Each customer is different

This is table stakes for targeted marketing and remains true for journey marketing. Define customer personas and personalize communications based on their preferences. Often, marketing is limited to single dimensional personas, ignoring vast amounts of contextual and interaction information available to a business. Almost all martech vendors today claim to be multi-channel, but in reality, limit marketers with fixed single dimension segments. Omnichannel marketers should make use of all possible data, cluster it across multiple dimensions and create micro-segments to truly understand and engage customers.  

4. Automate

Once customer journey maps, lifecycle stages, and personas are defined, marketing is ready to set up automated repeatable campaigns. This converts single-step, single-channel campaigns into multi-step, multi-channel campaigns. Journeys are dynamic, and automation should be able to account for different scenarios. For example, journeys should be able to trigger actions such as changing channels to elicit a better response.  

5. Measure

Next, marketers should have the tools to track performance against business goals established for each journey, for example, journeys might have been designed to drive customer engagement, move customers to the next stage or to drive sales conversion. Results from measurement should enable marketers to clearly identify journeys that are effective in driving goals.  

6. Optimize

Using data from past performance, and supplementing it up with Machine Learning algorithms can then identify best channels and best offers for a customer. Like anywhere else, personalizing for each segment is the key to maximize engagement, and account for different behaviors. Journeys that embed test & control and A/B testing capabilities are an excellent way to scientifically select the best variation and creatives, and truly understand the effectiveness.

Instore Real-time Personalization: Relevant, Contextual and Rewarding Customer Engagement

Pick up any newspaper and you will see hundreds of advertisement luring customers to one retailer or the other. Radio and TV blare jingles in tune with the brand promise of various products and urge the customers to engage with them. However, big budget marketing efforts as they are, how much of an impact do you think they make on an individual customer? Compare this to a personalized message that one receives on her mobile, identifying her as a distinct shopper, pre-empting her shopping need. The personalised message guides her to the best offer on the product/category that she is most likely to shop, and that too while she is still inside the store, trying to make up her mind on what to buy! Which of these above scenarios do you think the customer is more likely to respond to?

Achieving a Single Customer View in E-Commerce

What is a Single Customer view?

Till some time back, a single view of customer meant bringing together all data for customer and consolidating into a single record. Driving force behind single view of customer within an organization was usually operational. Marketing was merchandise driven and strictly followed quarterly planned marketing calendars and hence was content with only half updated or even outdated view of a customer. In the present scenario, businesses have become multi-channel. Customers now interact across a range of touch points. Marketing has become customer centric and is not content with an updated view of customer. They need to know each customer interaction and the intent of each interaction to personalize and ensure contextual relevance of each communication. For businesses today, the single view of customer means bringing together all data of customer including interactions, transactions and intent.

Data Challenge

Rise of digital commerce has resulted in not just huge data volume but also in new type of data that businesses have to deal with. Visitors can browse through the site, view products, read reviews without providing any personal information. Shoppers can interact with a brand’s social media properties, like posts, comment on them or share within their network. Visitors can browse through product catalog on the move through their mobile phones. These all are examples of data that is dynamic and relevant only for a limited time period and hence speed of capture and update is extremely important. Achieving single view of customer should not be looked as a one-time project, but as a continuous process of data persistence, update and correlation. Business use case behind the data types should help define the data capture process and technology.

Rise Of Contextual Marketing

Context is the key to relevance and personalized experience on e-commerce channels. Context can be geographical region, time of day, items or category you are viewing, brand or the price of item. Businesses that lack contextual personalization will soon risk customer attrition. The foundation for contextual marketing lies in real time integration of contextual data against every customer and having execution systems leverage this foundation to build personalized customer experience across digital channels. Contextual marketing brings along the challenge of real time update of single view of customer.

What are your options?

The path to single view is a long and arduous journey. Here are a few key points: – Manage multiple identifiers: Cookie data, device data, social handles, email ids, loyalty numbers – Maintain interactions per channel: Persist interactions per channel such as browsing details, purchase details, social likes and shares, etc – Continuously correlate data: Continuously look for common identifiers across data and collapse them. For example – use social login on ecommerce to collapse social and cookie data. Collapse cookies data with customer email address during item purchase. Use device id and multiple logins to build household information. – Identify actionable interactions: Identify interactions which are opportunities to provide contextualized marketing. Deploy real time integrations and actionable systems that can combine contextual information with customer past history to provide a highly relevant personalized communication. Businesses are becoming customer centric. A single view of customer, will be the most important asset that a business could hold to be successful in the new digital commerce era.