5 Essential Steps of Customer Data Orchestration
Solid digital marketing skills properly aligned with a brand awareness strategy can make your brand’s marketing efforts shine. Conversely, failing to do so can kill them. For this reason, effective marketing skills and data analysis is the major challenge that most brands face.
There is no shortage of data and advertising methodologies to choose from in today’s business landscape. Why then is effective marketing still a problem even for major brands? Even with coherent SEO techniques in place, what seems to be the real problem?
Simply put most organizations have enough data to analyze and make decisions, but their strategy breaks down when it comes time to turn data into actionable insights. The primary culprit is improper orchestration of all of the customer data at their disposal.
So, what is orchestration? Customer data orchestration is the process of collecting data from different channels. The data is then matched up with data from other existing sources and analyzed to better understand the full customer experience and journey.
With data orchestration, you receive the brand’s data and opinion from users irrespective of the device or tool that the indivudal is using to interact with your company.
So what does it take to achieve success in data orchestration?
1. Data Collection
How are you supposed to achieve perfect data orchestration if you don’t have data collection systems? As simple as it may sound, data collection is still a major problem for most organizations.
But first, where does this data come from? Every time a user engages with your brand on your website, this interaction yields a certain amount of data. The recorded data is then stored in the appropriate channels. That’s how it is supposed to work in theory at least. In reality there are often gaps that form when new campaigns, programs, or activities are implemented. Appropriate tracking tools are setup improperly or missing altogether and down the road this creates gaps in the data set available.
For data orchestration to be successful, you need to ensure that you get real-time data from these sources. This is because it reflects on real user experience with your brand.
2. Data Transformation
Remember, real-time data comes from different sources and channels. Depending on the awareness of your brand across various markets, the data is likely to be coming from a spread of various channels. If you’re a global brand, this data from different sources can even come in various formats and languages creating additional barriers.
To get the customer data you need orchestrated and aligned you need to create a single layer of data that is understandable and usable to make data-driven decisions. But how exactly do we achieve this? The data needs to be filtered and sorted out.
Similar data is then matched up to come up with a single data layer. Data transformation is a crucial stage when it comes to data orchestration.
3. Data Linking
Now that we have different layers of matched up data, what next? The data is from various channels and it needs to integrate into one system for effective analysis. Once aggregated, linking up the data will assist in developing the customer profiles.
Real-time data is from various clients accessing your brand’s website from different devices. Thus, it will be difficult for you to learn the customer’s identity. Data orchestration software will calculate the data and re-calibrate the data so that it matches up to a single customer profile.
Data orchestration software works to link data and customer profiles across different devices. It does this to create a single user profile and improve understanding of the customers’ experiences.
4. Associating Real-time Profile with Target Audience
After coming up with a real-time customer profile, you need to determine whether the profile qualifies as the target audience. Determine whether the profile fits the audience traits. Through this, you will know what strategies and marketing campaigns to apply.
It may be difficult to come up with a real-time profile that qualifies as the target audience, but it is achievable with the best data orchestration platforms.
You should note that the real-time profile is dynamic in that it is due to change based on the inbound data.
To achieve perfect customer data orchestration, you need to ensure that there is a profile that qualifies in the target audience.
5. Taking Action after Customer Data Orchestration
The final step is integrating the data orchestration platforms into the analysis and customer engagement technologies. Your data orchestration efforts will be fruitless if the data orchestration platforms don’t work in hand with your data analysis tools.
You will need to analyze the data to make appropriate marketing decisions. These data-driven decisions will be impossible to make if the customer data orchestration is not integrated with your data analytics tools. How will you engage your customers after the data orchestration?
Ensure that the customer data orchestration and customer support platforms are well integrated. This will play a huge role in determining the appropriate marketing activities to use. Also, you will be able to determine the best customer approach.
After data orchestration, it is important that the segmented data is well stored in secure drives, servers or cloud platforms.
Data security is another issue that needs attention. You need to not only protect customer data but the organization’s information as well.
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Customer data orchestration platforms provide the opportunity to curb major challenges, such as technological integrations and data fragmentation. For example, in the case of data fragmentation, the channels undergo a transformation and are stitched up into a single understandable data layer.
Customer data orchestration aims at improving the timing of offers, discounts, and promotions. Through it, you are able to determine the type of messaging of customers based on recent interaction with the brand.
Launching different campaigns across different channels can be difficult. It’s challenging to determine which segments are performing well.
Data orchestration helps better analyze and study each segment. Also, it helps you determine which campaigns are successful in which channels, helping determine which campaigns allocate marketing spend to.
The bottom line is that customer data orchestration aids in better analysis of data. It helps identify successful marketing campaigns and provides a better insight into the overall customer experience with your brand.
In return, you are able to know which marketing strategies to incorporate in the marketing strategy for your brand.