What is a customer-obsessed organization?

A customer-obsessed organization is one where the core focus is on customer needs and everything else in the organization is anchored around serving those needs. A few examples of customer-obsessed organizations are

• Google: “Focus on the user and all else will follow”
• Amazon: In the words of Jeff Bezos, “The most important single thing is to focus obsessively on the customer. Our goal is to be earth’s most customer-centric company.”
• Apple: In 1997 at one of the Apple’s Conference, Steve Jobs said: “You have to start with the customer experience and work backward to the technology. You can’t start with the technology and figure out where you are going to try to sell it.”
• Casper: The mattress start-up opened nap rooms (called Dreamery) in NYC to offer customers a 45 min nap and experience the brand instead of buying the mattresses based on simple touch and feel.
• Sephora: Allows customers to try virtual make-up at home using Augmented Reality. It also provides personalised product recommendations based on customer’s online and in-store browsing history
• Netflix: Leverages data to offer personalized recommendations to customers based on their interests and viewing history
• Wegman: A local grocery chain in the US with a huge fan following. It focuses on creating a great employee experience, who in turn create a great customer experience
• Southwest airlines: In 2014 when a Southwest flight was delayed due to bad weather conditions, the pilot ordered pizza for everyone on board — showcasing a great example of bottom-up customer obsession

Why is customer obsession important?

Customer obsession has a strong correlation with the business performance

• “A fundamental change of mindset focusing on the customer, along with operational and IT improvements, can generate a 20 to 30 percent uplift in customer satisfaction, a 10 to 20 percent improvement in employee satisfaction, and economic gains ranging from 20 to 50 percent of the cost base addressed in the various journeys” (McKinsey)
• “Acquiring a new customer is anywhere from five to 25 times more expensive than retaining an existing one” (Harvard Business Review)
• “Increasing customer retention rates by 5% increases profits by 25% to 95%” (Harvard Business Review)
• “66% of customers are willing to pay a premium for great experiences” (Salesforce)

What are the typical challenges of non-data led organizations?

The customers usually engage with an organization via multiple channels, such as Website, Emails, Mobile App, Social Media, Contact Centre, Online Chats, Physical stores/representatives. One of the biggest challenges which Enterprises face is the non-integration of data across these channels, which creates siloes and creates bad customer experiences across different sales and servicing touch-points, such as:

• Non-personalized and generic marketing reach-outs without understanding unique customer context
• Intrusive marketing (via SMS, phone, etc.) which is not well integrated with different customer journeys
• Context loss while customer service across different channels / different points in time, leading to customer frustration in explaining the full context to every time a new interaction is made
• Reactive customer servicing (when something wrong happens) instead of proactive customer servicing

What are the components of creating an intelligent and data-driven Customer 360-degree view?

Developing a truly effective and intelligent customer 360-degree view involves the following key components:

1. Integration of data across different siloes / channels such as

• Enterprise CRM data (e.g. for KYC details) and other Enterprise platforms storing customer transactions/other details (on-prem or on Cloud)
• Call center interactions
• Website browsing / Clickstream data
• Emails and chats
• 3rd party databases (with authority to share data under the right privacy safeguards), e.g. for Credit rating
• Social media (direct/indirect interaction with the Enterprise)

Integration across so many channels is achieved through Data integration tools (the leaders of Gartner Magic Quadrant being Informatica, SAS, Talend, etc.). Many CRM providers (e.g. Pega) with full-fledged CRM solutions also have in-built integration solutions across all the channels

2. Big data storage in Data Lakes / Data Warehouses: Given the large volume of data generated across so many channels, it is important to build a Cloud-based storage solution (via Data warehouses and Data lakes) to be able to use all the data available (instead of being limited by the capacity/high cost of on-prem data storage solutions). Snowflake, Microsoft, Oracle, AWS, etc. are some of the leaders in Gartner’s Magic Quadrant offering this solution

3. Intelligent Data Science engine built on top: Any data in its raw form is not useful unless processed and used for end business objectives. Some of the CRM providers provide an in-built intelligence engine (e.g. Pega with its Customer Decisions hub that offers a single source of intelligent decision making across marketing, sales, service, operations). The leaders in Gartner’s magic quadrant for Data Science and ML platform capabilities include SAS, TIBCO, Alteryx, etc.

How does an intelligent Customer 360-degree view help drive the customer obsession agenda?

With the 3 components (described above) in place, a lot can be done towards meeting the objectives of being a customer-obsessed organization, such as:

• Highly contextualized/personalized recommendations: The intelligent engine on top of 360-degree data can do micro-segmentation and recommend the right message, for the right customer, at the right moment and across the right channel (e.g. recommend a new product to customer depending on the signal of changing life events like graduation/marriage, or, based on the browsing pattern and real-time Clickstream analytics, offer a unique set of products for a customer). Netflix is a great example here.
• Truly omnichannel servicing: Context loss across channels is often one of the biggest dissatisfiers for customers. As an example, consider a customer registering a service request for a product replacement over a call center. If the line gets disconnected and the customer decides to complete the request over chat, the person (or bot) taking the request should already have the context of the previous interaction which the customer did over the phone, without needing the customer to repeat the full context again. This is a very powerful concept which is only possible if all the interactions go to a single integrated platform, irrespective of the channel
• Proactive customer servicing: An example is Freestyle Libre Continuous Glucose Monitoring System, which can capture and send data on glucose levels to an app on iPhone, Android, or Apple Watch. It lets the caregivers do remote monitoring and take proactive actions based on real-time data capture and integration with historical data of patients (to create a 360-degree time-series view)
• Customer churn prediction: The intelligent engine built on top of the customer 360-degree data can do predictive analytics to identify customers with a high probability of churn and recommend the next best actions to Enterprises (sales or service representatives) to engage with customers and retain them proactively.
• Risk reduction: This is highly relevant in the Financial Services sector, where a 360-degree view of data from both internal (e.g. transactions) and external (e.g. Credit rating, Politically Exposed Persons list, Utility bill payment history) sources can help the Enterprises drastically reduce their risks (e.g. related to lending, anti-money laundering, financial crime)