In 2020, meeting customer expectations is only half the battle. Scaling them is your top priority, considering the unpredictable and competitive the global market has been off lately. So, you must assess their preferences, predict their actions, and deliver the right sort of experience. But unless the enormous amount of data that flows through your applications, systems, and processes is unified, you won’t be equipped to do any of those.

Common data challenges

  • Difficulty in accessing data due to storage in silos across disparate locations, with middlemen systems/applications/processes
  • Data in inconsistent formats, which leads to detailed workflows to interpret them
  • Traditionally-slow and manual data collection, without inspection codes
  • Poor data quality, including duplication, due to manual or imperfect validation mechanism
  • Lack of data governance or stewardship that decreases the overall value of information

The problem is never the shortage of data. As mentioned earlier, the sheer volume of data in your organization can be staggering. Some of the common types include transactional data, master data, reference data, reporting data, and metadata that span across your customers, products, partners, vendors, and business users.

Instead, most of these challenges can be traced back to data unification, or rather the lack thereof.

Read: Top 5 data challenges CIOs face and how to solve them with MDM

On the road to unified experiences

As far as customers are concerned, from purchase history, interactions, browsing behavior, and service history. When juxtaposed with smart business rules, you can put yourself in a position to deliver proactive and satisfying customer experiences.

Your business workflows must also be configured to gather and leverage data from various touchpoints, such as email, social media, websites, in-store interactions, kiosks, and so on. You can use this data to develop segment-based campaigns and contextually target customers across the channels while creating competitive differentiation.

Build a layered data-driven strategy in the backend so that all the data that flows through your enterprise in a structured manner. It will also ensure that your cross-functional workforce leverage unified and consistent datasets.

The key is to make sure that there are no gaps in your data gatekeepers, be it applications, systems, or business processes. Instead of waiting until the post-data collection stage to start enrichment, you must create trigger points that enrich the data – as it flows.

What does this lead to?

Without contextual data, you won’t be able to meet your customer’s expectations at the granular level they want you to. That’s where data unification comes in. It creates data journeys across channels that converge in one place. That’s also where information, whether garnered through structured and unstructured interactions, turns into deep-dive insights that tell you what customers want, as well as how and when they want it.

Here’s what you can learn about your customers by unifying data:

  • Purchasing habits: What they have purchased, and what they may be interested in the most
  • Point of entry: What led them to your website
  • Demographics: Location, email, name, birth date, and other exclusive details
  • Social game: How customers behave on social networks and the type of content they share or interact with
  • Contact preferences: How they wish to connect with you
  • Third-party information: Personality traits, cultural values, lifestyles, etc.

Here’s what you can do by unifying your customer data

  • Create meaningful customer profiles, with a 360-degree view of each individual
  • Analyze and compare segment size, preference, and behavior
  • Personalize every interaction and increase conversion rates
  • Optimize your sales and marketing efforts and maximize the reach
  • Target the most loyal customers to increase the customer lifetime value

Other benefits of data unification

  • Reduce overall operational costs and workforce burden: By automating the data unification process, you can significantly reduce operational costs and enhance organizational scalability while ensuring disruption-free rollouts.
  • Improve business continuity: Before getting hit during times of crisis, you can regularly assess the performance of data integration and prepare for disruptions, without affecting your core operations.
  • Eliminate business risks: You can create an effective data governance strategy to put access control, change management, and data encryption processes in place while increasing responsiveness to data security threats

With the growth of agile methodologies and AI-driven technologies like robotic process automation and the simplification of master data management, new and more robust data unification strategies are emerging. Cutting-edge data analytics and machine learning tools are continually changing the game as to how quickly and accurately it can be done.

But the more immediate priority is that of delivering seamless customer experiences.

That’s the end game. And that’s where your focus should be.

Because of the emergence of customer-facing, digital-first brands like Amazon, Uber, and Zomato, and considering today’s pandemic situation, there’s no denying that we are slowly moving towards a digital-fluid future.

The key to unlocking seamless experiences lies in unifying data and harnessing the insights to personalize your interactions with customers, no matter when or why they reach you.

Read Article: Data 360 – Connecting the Data Dots with iPaas

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Dinesh Kesavan

Dinesh Kesavan

Dinesh is a passionate techno-marketer who understands the importance of technology in every facet of business and help customers to solve their business challenges with technologies (software & data) through marketing campaigns and programs.
Dinesh Kesavan