Behind every delighted customer lies great customer experience (CX). Behind great CX lies great business decisions, supported by great data-driven insights, based on great analytics. But you might not have great data analytics. Instead, you might feel like you’re just dealing with a data mess.
If you’re a data professional, you know what this looks like. Large amounts of disconnected, fragmented, often incomplete data spread across multiple systems and tools. The sources could be applications, email, social media, mobile apps, websites, chatbots, call centers, etc. None of this data can be useful unless it is combined and managed.
Having unprecedented volumes of data without being able to access it can be just as aggravating as having no data at all. Unfortunately, that’s the reality today. An Informatica survey found that more than half (55%) of CDOs report more than 1,000 sources of data at their organization.￼
This tells us in no uncertain terms that data deluge, spread and diversity are significant problems for enterprises today. For data to be ready for analysis, it needs to first be put through a process called data integration. This will bring it to a state where your business intelligence (BI) or analytics tool can generate meaningful insights from it.
For example, let’s assume the data on a typical customer named Anita is spread across:
- Klavio’s email marketing software
- Circles.so if they are part of the community
- Google Analytics, which tracks all their website logins and interactions
- Google Adwords and Facebook ads, showing what ads they engaged with
- Hubspot CRM for purchase and service history
No one system alone will give a complete picture of Anita’s behavior or preferences. However, integrating all the data into your cloud data warehouse, such as Snowflake, makes it possible to analyze the data, connect the dots and create an experience that Anita would value.
Data integration is a three-step process, which includes extract, transform, load (ETL) or extract, load, transform (ELT). The ETL process enables you to first extract the data from multiple disparate sources and systems. Next, you can transform the data by cleansing, joining, validating and standardizing it into a consistent format. And finally, you can load it into your choice of destination enterprise data warehouse. In the ELT process, raw data is extracted and loaded from a source to a destination data system, such as a data warehouse or data lake, and then transformed for downstream use.
A sound data integration process will provide you with clean, ready-to-analyze data collected from multiple systems and gathered into a single place. From there, it can be accessed by an analytics or BI tool of choice to generate reports and insights.
Here are five ways data integration can help transform that unseemly data deluge into customer insights, campaigns, experiences and, in the end, delighted and loyal customers.
5 Ways Data Integration Improves Customer Experience (CX)
Great customer experience is:
- Based on customer needs and preferences
- Personalized, timely and relevant
- Consistent across channels
- Linked to KPIs, such as higher retention, higher customer lifetime value, better net promoter scores and lower churn
Here are five ways the right data integration solution supports these CX outcomes.
#1. Drive operational efficiencies and streamlined customer data processes
Manual data gathering, wrangling and cleansing can be slow and error-prone. And creating ad-hoc data connectors and pipelines can be time-consuming, leaving the system unstable and the organization vulnerable to security lapses.
The right data integration solution that’s fast, easy and smart should automate the data integration process. This frees up the data team’s time to focus on more value-creating work. This includes mining insights and using them to create segments and develop campaigns and experiences that deliver tangible business results. Equally important, it removes data bottlenecks, that can slow down campaigns and go-to-market strategies, by making the right data easy to find and activate for business users.
#2. Leverage a single view of the customer
Customers today interact with brands over multiple digital and physical channels. This leaves a complex trail of data about their preferences, behavior and intent. Data integration helps create a single source of truth, or a 360-degree view of the customer, by bringing all the data generated by them across systems into one place.
This is not just a one-time activity. Ongoing data cleansing and transformation puts an end to marketing data silos. It also puts trusted data into the hands of business users when they need it. Empowered users know where to find and how to use the business data to their best advantage.
A single view of the customer becomes a catalyst for creating new and innovative ways to engage with customers more consistently and with greater relevance. It fosters cross-team collaborations and experimentation because when everyone is working with the same data, it’s easier to create a concrete action plan. The result? Better marketing offers, more meaningful sales discussions, quicker problem resolution and enhanced cross-channel interactions.
#3. Optimize campaign performance for higher ROI
When business users have access to high-confidence customer data, they can do a better job of defining customer segments, ensuring more contextual, relevant targeting and better personalization. Insight-driven decisions lead to better performance outcomes such as:
- Customer acquisition, cross-sell and upsell through improved profiling, segmentation / targeting and product recommendations by unifying data across customer, household, product, channel and activity
- Customer conversion with better-timed and more relevant, consistent and contextual cross-channel interactions
#4 Improve engagement throughout the customer lifecycle
High-quality, connected customer data can be used to drive more positive customer engagement beyond the campaign. For example, connecting customer, product and usage data can help streamline and speed up issue resolution and customer service. It can also improve the accuracy of churn prediction and enable your team to take proactive preventive action. And it can enhance next-best-action recommendations to drive retention.
With easy and fast data integration, your customer-facing teams can experiment with and increase customer engagement across new channels like social commerce, shoppable ads and in-store experience digitization channels with confidence, knowing the data generated will be actionable.
#5. Ensure a positive privacy experience
Privacy matters a lot today in customer experience, including how their data is collected, managed, processed, shared, stored and destroyed. Regulations around data privacy and security are getting more stringent, and customer awareness about data rights is growing. News of a data breach can bring not only a regulatory fine but also can negatively impact brand credibility.
Using a proven data integration tool to move join, cleanse, transform and load data into a BI or analytics tool without compromising on data governance or security helps to build brand credibility. It also helps ensure that data is being used in compliant ways and that sensitive data is being protected from unwanted exposure during collaboration and consumption.
Not All Data Integration Tools Are Created Equal
While the impact of data integration on CX outcomes is significant, remember that not all ETL and ELT tools are created equal. Unfortunately, given the high cost and/or complexity of many data integration tools in the market, data professionals may end up using open-source or stand-alone tools. This likely will support only ad-hoc or partial use cases. If IT is too busy to help, data professionals may end up hand-coding manual connectors just to get urgent jobs done. This might work in the short term, but the long-term costs may not be worth the effort.
The ideal data integration tool should be easy to use to enable tech-savvy marketing ops professionals to self-serve the solution with no code and no central IT help. It should be proven, i.e., secure, enterprise-grade, stable and reliable at any scale. And it would simplify rather than complicate data management and, importantly, be free or low-cost to avoid cumbersome budgetary approvals.
Data integration tools like Informatica Cloud Data Integration-Free and Cloud Data Integration-PayGo are easy, cost-optimized, and proven data integration tools. They eliminate the need for patchwork and workaround, ongoing IT support and budget approvals. At the same time, they deliver just about everything data practitioners need to support the organization’s CX goals at high speed.
Learn more about how to easily load, transform and integrate your data at www.informatica.com/free-paygo