Everything You Need to Know About Customer Data Integration

Marketing data integration: what is it and why do you need it?

Consider this: You want to get a holistic view of which conversion funnel is providing the best results. But you have traffic data in Google Analytics, customer data in Salesforce, and lead data in HubSpot. Moreover, your video recordings are in Hotjar, sales numbers are monitored through MixPanel, in-store analytics data is collected through Wi-Fi and stored on a separate data mart, and in-store path analysis is stored in a third-party system.

How will you find and optimize data for the best customer journey on both ground and web?

This Is Where Customer Data Integration Comes In.

Customer data integration is one of the most crucial aspects of any business. Without proper customer data integration, it is nearly impossible to get accurate, consolidated insights into your buyers, and without those, mapping the customer journey becomes a struggle for marketing and sales teams.

In this article, we will discuss why customer data integration is important and how you can use it to realign your business focus, and most importantly, can customer data integration impact business efficiency?

The topics that we will discuss include:

  • What is Customer Data Integration?
  • Why is Customer Data Integration Important?
  • Customer Data Integration Best Practices
  • Which Customer Data Integration Tools to Use?

So, let’s get started.

What is Customer Data Integration?

A business gets customers from multiple channels. Each customer uses certain touchpoints before reaching the final stage of the conversion funnel. This is usually the lead form/purchase page/query or contact form.

The multiple channels that customers use can be social media, organic search, referral traffic, offline search, word of mouth, or a cold call. There can be many more depending on what type of marketing channels a business uses. For enterprises, inbound channels can be more than a dozen.

The touchpoints that customer contacts can be: Blog, landing page, white paper, eBook, checklist, template, infographic, datasheet, comment, answer box, live chat, and many others. These are the interactions that customers make before deciding if they want to move forward with the purchase.

Customer data integration involves collecting data from all these sources and consolidating them on a single database. The goal is to offer internal users a single data view for reporting, analyses, and visualizations.

This data can then be used by business analysts to ascertain the best customer paths for business intelligence. Consequently, C-level executives can get a holistic view of the overall customer lifecycle so they can make better strategic business decisions.

Why is Customer Data Integration Important?

Customer data integration is vital for getting a 360-degree view of the customer journey and finding a single version of truth (SVOT).

It helps:

  • Marketing analysts learn about the flaws in their funnels, where anomalies occur, and what they can do to fix or improve them, ultimately enhance the customer process
  • Sales professionals learn about what methods and approaches they can adopt to close deals faster. It also helps them distinguish interested leads from junk leads
  • Business analysts learn about customer paths through various funnels, using their insights to create forecasting models, and streamline the purchasing processes
  • C-level executives to get the whole picture and make relevant business decisions that can move the organization forward.

Customer data integration leads to customer journey optimization, which is a continuous process to improve lead quality and drive customer loyalty.

Customer Data Integration Best Practices

Every company has its own customer data integration process but even if your company doesn’t have one or you are still struggling with creating one, follow these best practices to not miss out on the vitals.

1. Identify All Source Points

Make a list of all the data sources where your customer data is stored. This can be tools, databases, or even text files. Web-based tools such as Salesforce, Marketo, and Google Analytics keep website traffic and purchase data. If you also get customer orders from your social media pages, download that data in PDF files. You can use report modeling software to create structured data from it. Astera Centerprise, a leading customer data integration platform, also offers built-in report modeling features that you can use to create structured data from unstructured file formats.

2. Consolidate Data On A Single Storage

Once you have identified all the data sources, move them all to a centralized repository such as a data warehouse or data mart. You will need data connectors for sources that are not compatible with your current data warehouse. In that case, use an ETL tool that offers custom connectors to consolidate the data. Astera Centerprise also offers ETL and ELT functionality for moving data to the database.

3. Define Integration Goals

It is important to have an integration goal from the start. It will be based on the insights you want to extract and then forecasts you want to be done. The integration goal will also help you find the relevant OLAP tools that you will use for creating data visualizations. If a goal is not set prior to the customer data integration process, problems can arise, such as incomplete data getting ingested to the data warehouse or not integrating data from all data sources. The best way to avoid that is to have a goal on paper.

4. Create Evaluation Timelines

Similarly, create an evaluation timeline for assessing the customer journey. This will be the time when your team or the decision-makers get together regularly to make sense of their data through visualizations and recommend steps for improvement. These meetings can be conducted monthly, quarterly, or even biannually. The evaluation timeline will ensure that all integrations are complete before the deadline.

5. Automate Customer Data Integration

Finally, automate data integration tasks so that no additional human resources are specifically hired for this process. The automation will include extracting data from identified data sources, transforming them, and then storing them in the data warehouse. Automate the whole process and put it on a schedule based on your timeline.

6. Comply With Data Regulations

Customer data integration involves removing unnecessary data that is not of use to you for process improvement. This means removing Personal Identifiable Information (PII) and Personal Financial Information (PFI) before storing it in the data warehouse.

7. Decide User Level Access

Make sure to create user levels based on each resource’s designation and grant them access to the areas that they require for their daily work. This will ensure data integrity and confidentiality.

Start Customer Data Integration with Astera Centerprise

Now that you are aware of how the customer data integration works. It is time to get a customer 360-degree view of organizational data. The best tool for the job is Astera Centerprise because it offers a wide range of connectors for data extraction from legacy, on-premise, and cloud data sources. It also offers workflow automation and job scheduling to make it easy to move data through the customer data pipeline.

Learn more about how Astera Centerprise can help your organization make the best use of customer data.

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