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May 2, 2018

6 Key Stages to Successful Data Orchestration

By Jay Calavas, Tealium

180502 Tealium 6 Key Stages To Successful Data OrchestrationThe concept of Data Orchestration is a new one and has yet to clearly be defined to the industry. I have my own unique view and want to provide a simple guide to achieving this goal. Data orchestration is when a brand is receiving real-time data and insights on a user no matter the device, tool or technology they may be interacting and engaging with. Data orchestration helps to solve the challenges of data fragmentation, organizational silos, technology integrations that don’t speak the same language, and ultimately, poor customer experiences.

So how does a brand looking to find solutions to those challenges implement data orchestration within their organization?

I believe there are 6 key stages to successful Data Orchestration:

  1. Collection
  2. Transformation
  3. Enrichment and Stitching
  4. Audience Association
  5. Action
  6. Ownership

Each of these stages contains some significant requirements and as we know not all technology is created equal. So let’s take a look at each stage in detail:

Data Collection

While it may seem simple on the surface this is one of the biggest Achilles heels of most technologies.  Any system can put a tag on a website or upload a file but data collection is far more complicated than that. Let’s talk about where data is created. A customer might be engaging with your brand on your website, mobile app, call center, in-store, kiosk, chat, smartwatch or any number of channels. Each of these interactions in each channel results in data being created and put into silos. To check the box for this stage; you need to be able to collect data in real-time from all of those sources.  

Transformation

With data being collected from all of these different sources and channels you can assume it’s not in the same format or language. As data is flowing in, we must apply transformations to the data to cleanse and blend it into a single data layer. Remember, preparation is just as important as any other stage of the process! Matching data and making it ready for the next step is essential and, without it, the rest of the process is broken.

Enrichment and Stitching  

Once we have a fully correlated omnichannel data layer, we can begin creating a single view of the customer. The key is to do this in real-time at the point of data collection vs. after the fact. Doing this takes some technical savvy, but if you choose carefully, some platforms can run inflight calculations and models on inbound data and enrich the visitor profile right there and then.  

Furthermore, identify resolution comes into play if we are genuinely doing this sort of real-time enrichment. Upon identification when we find a device that belongs to another profile we need to stitch them together. The key here is not just to ‘link’ profiles but to recalibrate and calculate all of the enrichments to account for everything we know about two different devices. Tricky but achievable!

Audience Association

If we have a real-time profile that is addressable for in-the-moment engagement we need to qualify this profile in and out of audiences, so we know what actions and campaigns to apply to them. In reality, this is just another level of enrichment but is also the final profile based orchestration before we turn to other tools. This isn’t a segment, it is a ‘current state’ of that profile and can dynamically change as fast as the data flows in.

Action

Any platform playing in the Data Orchestration space must have real-time integrations into the tools that you use to analyze and engage your customers. Think API’s and marketing tags to start. Number, scale and depth matter here, don’t just look at a logo slide – dig into the details.

Ownership

All of this heavy lifting should result in the syncing of this data to your Data Lake and Data Warehouse. You will get a standing ovation when you tell those teams that they are going to get a real-time feed of fully correlated cross-device, omni-channel customer data.  

These 6 stages are key to successful Data Orchestration. I believe these are core competencies that remove all of the batch processes from legacy approaches to data.  Real-time in the realest sense – companies are entering the golden age of data.

Wanting more information on Data Orchestration? Watch our on-demand webinar to learn more about what it is, how it helps achieve the single view of the customer, the difference between Campaign Orchestration & Data Orchestration and so much more.

The CDP Institute educates marketers about the issues, methods, and technology used to manage customer data, with a special focus on Customer Data Platforms. Join the CDP Institute for free access to valuable information and insights.

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