What is Omnichannel Strategy?
Omnichannel Strategy is the 360 Degree Customer Data Unifying Process from all the Channels, Platforms, and Devices to provide One Single View of Customer that helps in Higher Degree of Customer Engagement, Personalisation, Relevance and Higher Returns on the Various Marketing Activities. Based on Research, it is generally observed that Omnichannel Strategy can bring in nearly 4-5 times more sales than Single-Channel Marketing.
This is Achieved because of Seamless Messaging Across the Channels, that create a Coherent, Consistent and a Unified Message for your Brand from the first touchpoint (Example Online-Web or Mobile App or In-Store) to the last (Example- In-Store or Online E-commerce Store) with Regular Hyper-Personalised triggers, Notifications and Messages prompting the Customer to Shop or Purchase or Explore a Recently Launched Product.
To Ensure 360 Degree Seamless, Consistent and Integrated Shopping experience, the Data needs to be regularly updated from all the Channels, Platforms, and Devices and Relevant Consistent, Personalised Messages or Promotions need to be Pushed Across all Channels based on the analysis of the Customer Data.
Why Do You Need Omnichannel Strategy ?
Providing consistent and seamless customer experiences across all channels has become essential for businesses today. With customers expecting to interact with brands in multiple ways, companies must meet their demands to stay competitive. Research has shown that customers who engage with companies across various channels tend to spend more than those who use only one channel. Additionally, customers who use omnichannel methods have atleast 30% higher lifetime value compared to those who use just one channel. However, following are the specific reasons why we need Omnichannel Strategy.
- Research and Studies have also shown that Companies that have implemented strong omnichannel customer engagement strategies are found to retain around more than 70% of their customers, while those without such strategies only retain 30%. Therefore, adopting an omnichannel strategy can significantly improve customer satisfaction, increase revenue, and offer a competitive edge to businesses.
- Better customer experience: According to a survey by Salesforce, 84% of customers say being treated like a person, not a number, is essential to winning their business. An omnichannel strategy ensures that customers receive a personalized and seamless experience across all touchpoints, leading to increased customer satisfaction and loyalty.
- Increased sales: A study by IDC found that omnichannel shoppers have a 30% higher lifetime value than those who shop using only one channel. By providing customers with multiple channels to interact with your brand, you increase your chances of making a sale and driving revenue.
- Improved inventory management: With an omnichannel strategy, businesses can gain better visibility into their inventory levels and manage it more efficiently. This leads to reduced stockouts, lower inventory costs, and a better customer experience overall.
- Use cases and examples: Many businesses have successfully implemented omnichannel strategies and seen positive results including Starbucks, Sephora, and Nike. Starbucks has implemented a successful mobile ordering and payment system and their mobile app allows customers to order and pay ahead of time, leading to a 10% increase in revenue and a 20% increase in mobile payments. While Sephora offers a seamless experience across its website, mobile app, and physical stores and Beauty Insider program allows customers to earn points for purchases made in-store, online, and through mobile devices. This has led to a 40% increase in loyalty program members and a 24% increase in sales. Nike has also implemented an omnichannel strategy that includes personalised marketing campaigns, in-store experiences, and a mobile app.
Examples of Omni-channel Marketing Strategy :
- A Push Notification on the Mobile App or an SMS Message when a Customer Purchases a Product/Shops in the Physical Store
- A SMS Message or Push Notification (Carrying an Offer or a Product Promotion) to the Customer to Purchase or Shop as soon as he connects to the Free Wifi of the Brand (in the Physical Store).
- Retargeting Messages to the Customer (on Social Media) for the Product they Researched about on the Google or the Product they abandoned in their Online Shopping Cart.
- Email Campaigns with Promotions, Discounts and Coupons to the Prospective Customers.
- Mailer Campaigns to the Prospective Customers with Discounts or Coupons.
How to Trigger Next Best Action in a Omnichannel Platform ?
Analytics is at the Core of Next Best Action Recommendations in any Omnichannel Platform. This Requires Analysis (Extending to Machine Learning based Predictive Analytics, Propensity Scoring Algorithms like Propensity to Buy, Respond to Campaigns etc.) of Customer Data to Extract Insights, Trends and Recommendations on What Should be the Next Best Course of Action for any Customer. This Whole Process is Accomplished by Optimizing and Unifying the experience for each customer across Channels, Platforms and Devices along their respective Journeys by coordinating between different departments like Business, IT, Customer Support, Sales, Marketing and Finance and Breaking the Silos within and across each of the Departments to unify the Customer Data
Next Best Actions are one of the Most Important Triggers in the Customer Journey, Set in the CRM Systems in order to be more efficient and Proactive in Responding to the Customer Needs to drive Higher Customer Satisfaction, Higher Customer Engagement by providing Unifying and Seamless Experience for the Customer starting from the first touch point to the last touch point (The Point of Customer Purchase – Online, Mobile App or InStore) across Platforms, Channels and Devices.
Examples of NBAs (Next Best Actions for Customers)
- SMS Triggers, Reminders, Notifications (NBA): Emails (with Gentle Reminders of the Products and Services based on the Hyper Personalized Data, Offers, Promotions of Products or Services or Discount Coupons (Via Mobile App or Social Media)
- Customer Analysis – Analyze the Customer Behavioural Data Across Channels, Platforms and Devices to have an better Understanding of the Customers and Generate Customer Reports or Create a Performance Dashboard- How they Spend, How they Respond to Campaigns, Transaction Trends, Purchase Path and Behaviour, Products or Services of Interest, Pain Points (based on Messaging and Interaction between Customer and Sales or Support Teams). Identify the Customer Attributes to decide upon NBAs based on their Interaction and Transaction Data.
- Customer Segmentation: Segmenting Customers based on their Behaviour and Demographics with Hyper Personalised Messages and regularly updating these Segments with fresh data.
- Customer Scoring Models or Alogrithms – Having a Predictive Scoring Model/Algorithm for each and every Segment of Customer and Updating these Models Regularly with Latest Scores. These Models Can be Predictive ( What the Customer is likely to Do Next or Buy Next) or Prescriptive (Next Best Action) – Most Common Example here is Personalized Discounting or Loyalty Mechanism in Retail Supermarkets or on Ecommerce Platforms like Amazon or BestBuy etc. Rank Order the Customers based on these Scores to Create an Order of priority for a Follow Up Call or Sending an Email with Personalized Content or even Offer based on the Individual or Customer Segment Score.
- Real time Analytics based Next Best Action Framework: To Generate Triggers and Insights based on Real time Customer Interaction with Chatbots or Online Customer Support Teams. Example – Sending them a Coupon or an Offer based on their Product of Interest and their Request for Lower Price on a Specific Product or Service- Instead of Declining their Request, sending them an Offer or a Coupon in order to Gain a New Customer or even Retail an Old Customer. Another Example is Prompting a Customer in Real time (Immediate Email or through Chatbots) to Complete his Purchase of the Product in the Shopping Cart to lower the Cart Abandonment Rate.
Designing a Scalable Omnichannel platform (What does it take Design a Scalable Omnichannel Platform ):
1. Breaking of the Department Silos :
This involves Free Flowing Information Exchange between Technology, Sales, Marketing, Customer Service, Finance Departments without Ego attached to the titles and who does what and sits where in the Hierarchy. This is the Biggest Bottleneck in Designing a Scalable Omnichannel Platform and most Organizations Struggle here as this is the Core Point that Facilitates Digital Transformation with Upgradation of the Tech Infrastructure. If you struggle here, its very likely that you will also struggle in the next point.
2. Technology Infrastructure
As Data storage Requirements Increase and Require Unification of Data from multiple sources to create a 360 Degree Customer View, it involves complete Digital Transformation. As such IT Infrastructure has to to incorporate cloud based Solutions. The Technology Infrastucture with Regards to Omnichannel Strategy can be further Broken by Team Functions and respective tasks handled by each team:
- Systems Engineers or Tech Architects: These Professionals Blueprint the Entire Tech Stack – Hardware and Software Requirements (Web App and Mobile App) and Create a Holistic Strategy with Regards to Each and Every Component of the Technology Stack- Be it Operating System, Database, Softwares, Programming Languages, Cloud Platforms, IOT (Internet of Things) etc.
- Data Engineers – These are the Ones that handle Data Preprocessing, Data Storage or Warehousing and get the Data Ready for the Analytics and Data Science Teams. Data Engineers are primarily tasked with Managing, Processing and Storing Data at the Back End using different Commercial Data Platforms or even Open Source Back end Solutions.
- Business Analytics Experts – These are the Ones that Define a Business Problem or Objective in line with the Next Best Action and handle Prescriptive Analytics (Data Based Recommendations on Business Strategy). Their Primary Task is Data Analysis,Creating Predictive Modeling Pipeline and Strategy based on Desired Business Outcomes, Architect the Blueprint for the Data Pipeline or Analytics Framework – How it will Consume Data, Type of Data, Data Transformation, Defining Business Objective and Modeling Strategy (Type of Model – Campaign Response Model, Cross Sell Model, Up Sell Model, Propensity to Buy, Churn or Default Model etc.), Descriptive and Prescriptive Analytics. These are Typically Professionals that have Considerable Understanding of Business, and Analytics Solutions based on Descriptive and Prescriptive Analytics.
- Data Scientists – Are the Ones that write and Implement Data Solutions, Scalable Machine Learning Algorithms for different Use Cases based on Inputs and Suggestions from Business Analytics Experts and or Parse humongous amount of Information on Social Media using NLP and Produce Actionable Insights and Reports. They are primarily tasked with Productionising and Automation of the Predictive Models, Data Reports and Insights and Manage the Intensive Coding part of the Data Science Models dealing with Automatic Trigger based Next Best Actions for the Marketing or Sales Teams (which are Routed Via Business Analytics Experts)
Omnichannel Customer Journey Stages with KPIs for Each Stage
The Omnichannel Customer journey can be broken into the Following Stages based on the Customer Interaction with the Brand/Business across the Channels, Platforms or Devices.
- Online or Instore Visitor (Brand Awareness): The First Touch Point when a customer shows Interest and/or first discovers your Value Offering by either Visiting the Offline Store or on Social Media or by Visiting the Website or Downloading the Mobile App. This is the Area of Brand Awareness when a Prospective Customer becomes aware of your Brand for the First time based on Some Specific Product Requirement or just a Random Reason (Driven by Impulsive/Instinct of the Customer on the First Impression of the Product or the Brand). KPIs that Measure the Success of this Stage is Total Visits, Total Unique Visitors, Total App Downloads, Average Time Spent by a User,
- Repeat/Trial Visitor (Brand Research/Trial) : This is a Point When a Customer Repeatedly Comes to your Website or Store based on his Expanding Interest and Curiosity and Brand Awareness but still not signs up officially for Regular Updates. Main Focus is to Research about Products or New Services.
- Observer of the Brand/Subscriber (Brand Engagement): When a Customer Signs up for Regular Periodic Updates on Products and Services or even General Content around the Business Domain. This is driven by Product Advertising and Promotions, Instore Display, Relevant Content Marketing around Specific Business or Product Topics based on the Area of Interest or Regular browsing of Products and Services of the Brand by repeat visits to the Website or Mobile App or Physical Stores to checkout the latest Productions or Promotions. This is facilitated by having a Solid Customer Engagement Strategy with Regular Triggers using SMS, Email Campaigns or even Coupons to Convert the Window Shopper into a Product Purchaser.
- Shopper/Customer (Conversion): This is a Touch point When a customer purchases a Product or a Service from you based on the Previous Pre-Sales Steps in the Customer Journey. From a Business Perspective, this is called as Customer Acquisition or the Point when a Business or a Brand Acquires the Customer based on their Intensive Efforts around Customer Engagement, Promotions, Advertising, Social Media or Content Marketing.
- Repeat Customer (Customer Retention): When the customer Purchases the Products or Purchase for the Second time based on Great Experience of the product or Service. This can also be Need Based, or driven purely by the Power of the Brand Promotions or Advertising, Newly Launched Product or Service of the Brand, Effective Customer Engagement Strategy both Online or Offline . Generally the Brands need to balance between Cost of Retaining a Customer and Cost of Acquiring a Customer as Cost of New Customer Acquisition is Quite High for most of the Businesses. So one has to have a Solid Post Sales Strategy to keep the Customer Engaged Happy and Satisfied (with post sales Customer Support if he runs into issues) and Regularly updated (via SMS, Email, App Notifications, or Social Media Posts) with Hyper Personalised Content based on his Area of Interest, Promotions, Offers or New Product Launches.
- Loyal Customer: To ensure higher profitability, it is Inevitable that Brands and Businesses Invest in the Area of Post Sales Customer Support and keep the Customer Relationship as the Focal Point of their Omnichannel Strategy to ensure Higher Customer Satisfaction and Seamless Experience for the Customer. This can Convert a Repeat Customer into a Loyal Customer (the one that buys periodically and repeatedly) leading to a Higher CLV (Customer Lifetime Value) and subsequently Resulting in Higher Revenue and Profits.
KPIs for Omnichannel Customer Journey
- There are several key performance indicators (KPIs) that businesses can use to measure the success of their omnichannel customer journey. Some of these KPIs include:
- Sales Conversion Rate: This measures the percentage of customers who make a purchase after interacting with a business across multiple channels. By tracking this metric, businesses can determine the effectiveness of their omnichannel strategy in driving sales.
- Customer Satisfaction Score (CSAT): CSAT measures how satisfied customers are with their overall experience with a company. By measuring CSAT across all channels, businesses can determine if their omnichannel strategy is delivering a consistent and satisfactory experience.
- Customer Lifetime Value (CLV): This measures the total revenue a customer generates throughout their entire relationship with a company. By tracking CLV, businesses can determine the effectiveness of their omnichannel strategy in retaining customers and generating revenue over time.
- Customer Retention Rate: The customer retention rate measures the percentage of customers who continue to do business with a brand over a specific period of time. This KPI can help businesses measure the success of their omnichannel strategy in keeping customers engaged and loyal.
- Net Promoter Score (NPS): NPS measures how likely customers are to recommend a company to others. By tracking NPS across all channels, businesses can determine if their omnichannel strategy is creating loyal customers who are willing to advocate for their brand.
- Average order value: The average order value measures the average amount spent by customers across multiple channels. This KPI can help businesses identify which channels are most effective in driving higher order values.
- Time to resolution: Time to resolution measures the time it takes to resolve customer issues across multiple channels. By monitoring this KPI, businesses can identify areas for improvement and ensure that customers receive timely and effective support.
What Is Omnichannel Personalization?
Omnichannel personalization involves using data from multiple sources, including customer interactions, purchase history, and demographic information, to create a unified view of each customer. This data is then used to personalize the customer’s experience on each channel they use to interact with the brand, such as email, website, social media, mobile app, and in-store.
For example, a customer who frequently purchases running shoes on a brand’s website may be sent personalized product recommendations for running gear via email. If the same customer visits the brand’s physical store, the sales associate may use their purchase history to recommend related products or accessories.
A retailer may use a customer’s purchase history to send personalized promotions via email or direct mail. For example, a customer who frequently purchases children’s clothing may receive a targeted promotion for a sale on kids’ clothes, while a customer who has never purchased children’s clothing may not receive the same promotion.
A company may use a customer’s purchase and service history to provide personalized customer service across all channels. For example, a customer who had contacted the Support Center of a Company for an issue with a product may receive personalized follow-up emails or phone calls to ensure their issue has been resolved.
A company may use a customer’s previous interactions with their mobile app to deliver personalized content and promotions. For example, a customer who has previously purchased musical event tickets through the app may receive personalized recommendations for upcoming musical events.
