There’s a lot of talk these days about data driving your customer experience (CX). You and I benefit from it but what does customer experience really mean? In simple terms, customer experience is about creating value for people and organizations by transforming customer journeys with a variety of customer-first goals, strategy and design decisions, business process changes, data, technology, organizational alignment, change management, and key metrics.
You’re in the CX Business
Every company, from a startup to Fortune 100, is in the customer experience business. The reason being is customers make purchasing decisions and recommendations — in the moment and the future — based on interactions they have with your brand. Customer experience goals are easier to achieve when strategies are created and executed to address what customers want when they want it, rather than how businesses are organized or currently operating.
Most business leaders today know it’s no longer enough to compete with just their products and services. Companies who focus on delivering value and competing with customer experience are, at their core, innovating continuously, harnessing customer data in real-time with technology enablement to deliver personalized, delightful experiences for people.
Good customer experience leaves people feeling heard, seen and appreciated. It has a tangible impact that can be measured from a revenue perspective. In a recent study about experience from PwC, with a representative sample of 15,000 survey respondents from 12 countries, 73% of all people point to customer experience as an important factor in their purchasing decisions. Yet only 49% of U.S. consumers say companies provide a good customer experience today.
Drive Meaningful Experiences by Knowing What’s Important to Customers
I recently connected with Raghu Murthy, founder and CEO of Datacoral in San Francisco, to discuss how data innovation is helping to create and drive meaningful customer experiences. Murthy said, “as a consumer, a lot of what I think about when it comes to customer experience is — where am I spending my time?”
Murthy touched on one of Datacoral’s customer success stories, MealPal, as an example of a data innovator focused on customer experience and ecosystem value creation.
What is a data innovator? “It’s when every single function within the company comes together around the data they have,” said Murthy. “It’s also about how they build the product, how they learn what their customers are doing with the product, and how they market and sell the product.”
“MealPal has leveraged data so well to make my customer experience awesome, said Murthy. “They are one of the few and growing data innovators out there.”
SaaS Applications like MealPal Benefit from Datacoral’s Innovation
Datacoral helps MealPal create the fuel for their digital business, which not only provides restaurants with a valuable extension to their lunchtime rush by adding a flow of pre-paid, take-out customers, but also gives them feedback based on customer behaviors and meal preferences with data collected through MealPal’s application and refined, published and delivered through Datacoral’s data pipelines.
Customers get a delicious, affordable, eat-at-your-desk meal, and restaurants gain better customer profile data along with an increase in take-out traffic, without disrupting their onsite dining business. A win-win situation for everyone involved in the experience.
SaaS Companies Rely on Datacoral
SaaS teams choose Datacoral because the company provides the shortest path to operationalize continuous data value going to consumers, machine learning models, and corporate systems. Datacoral does this by automating the ongoing end-to-end lifecycle of data pipelines. This enables SaaS organizations to quickly create value and compete on the merits of their analytics, and how they leverage the platform.
Datacoral Reduces Time and Cost to Value
Datacoral helps customers eliminate the pain of slow and expensive value delivery for the data they generate, hoping to fuel their businesses. The company helps them reverse and accelerate this cost to value ratio by enabling continuous flow of data from original source to their value destination points, where needed by data consumers like business intelligence analysts and data scientists as well as publishing data that drives customer value in operational systems.
Traditional data delivery pipelines are painstakingly constructed by data teams using multiple tools in support of complicated, multi-stage transformation processes. This outdated approach is time consuming and expensive, and results in low-value, slow flow of the trusted, refined data that is necessary for providing meaningful customer experiences.