How to Consolidate Your Data for Successful Marketing

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How to Consolidate Your Data for Successful Marketing

Data is the driving force of major businesses today, and with companies taking their marketing front to the digital or online space, the rate of data acquired is increasing stupendously.

So, to ensure that the marketing data is managed well and used effectively to help businesses thrive, some steps must be taken mandatory. Undervaluation of data will harm your business by depriving you of complete understand ability of your customer’s behavior.

You can give a consistent experience to your customers only when you are collecting, reviewing, and analyzing the data of all platforms under one centralized space. Hence, this is the only thing that can ensure consistency. And this is what we call data consolidation!

Let’s dive deeper into data consolidation, its effectiveness, and the best practices to implement it for productive marketing benefits.

Understanding Data Consolidation

Take data consolidation as a step after data integration. The purpose of implementing a data consolidation strategy is to integrate and combine the data from various sources into a single place for setting up a unified view and determining analytics.

Today, every organization is data-driven, receiving data from various channels, including 3rd-party vendors, several departments, and multiple databases, which should then be combined to analyze.

You need a better view of how your target audience responds to your brand’s services and offerings. Therefore, data consolidation is of utmost importance.

With it, businesses can streamline the data resources, determine patterns of interactions, get actionable insights and have a 360-degree view of business assets with all data in one place.

Data consolidation is of two types, data virtualization and data warehousing. Data virtualization is a unified process of combining data from various sources without moving them. It is a complex process, but it saves much of your space, as you won’t store the data twice. Here, data stays in its place and is only virtually retrieved through tools before it can be combined with other specific datasets.

Data warehousing is about importing data from various sources and storing them in a central location. Maintaining uniformity of data is seamless with data warehousing.

Best Practices or Techniques of Implementing Data Consolidation

When there is an abundance of data from various channels, the need to maintain the accuracy and quality of data is of utmost importance. With data consolidation, all discrepancies are extracted from data before they can be used for analysis or reporting. Hence, you will save a lot of time and increase the efficiency of marketing results from the data acquired.

To ensure you avail them all, the market best practices or techniques for implementing data consolidation are:

  1. Combine the APIs

The first and most important thing to look for is combining the APIs. Data consolidation is considered effective only when your business data is consistently processed or uploaded to a singular platform. You can do it manually by sourcing the data from various channels, but by the time you finish doing it, some of such information will be outdated.

You need real-time data, and that is possible only when you combine all the APIs from all your data sources and link them to the unified dashboard. Hence, you don’t have to manually do the task and will have access to real-time and updated data at all times. Thus, marketing data analysis and optimization will be easier and more effective.

There are several technologies out there that have dedicated features to enable you to share and communicate the data among all software solutions. All you have to do is attain flexibility on how all other software solutions share data. You should try and adapt this if combining APIs isn’t possible in your case.

  1. Ensure Completeness of the Data

Utilizing the technologies to share or merge the data is one effective solution to help you ease the task. But at the same time, if the data seems incomplete, but you are transferring it anyway, your business might experience some issues with concluding.

When you don’t have complete information about your leads or customers, there might be some form of organizational issues in the long run. Suppose you use a CRM that categories the leads through their email address. If the data you are transferring to your unified dashboard is missing an email address, then the tool might face a problem distinguishing or categorizing the specific leads.

Hence, you won’t be able to run your assessments with precision. Therefore, while you are considering data consolidation, ensure all fields are filled out before you integrate with any of such processes.

  1. ETL (Extract-Transform-Load) and ELT (Extract-Load-Transform)

ETL is one of the most popular techniques for implementing data consolidation. It is the easy process of extracting data from various channels while transforming it into the right format and storing it in a specified destination. The best part is anyone using any tool can access this stored data.

ELT is another popular method, similar to ETL, but it has a minor difference. There is no need to transform the data before loading or storing it. You can consider storing the data as you receive it from various channels. Anyone or any tool needing access to this data should do the transformation from their end.

ELT is useful when different departments within your organization or any other company need to access the data. But again, it depends on you and your organizational team to decide which method suits your data consolidation needs the best.

  1. Hand-Coding Technique

Hand-coding is one of the many manual processes in which an expert is handed over the duty of building scripts to extract data from various channels to consolidate them. You need an expert from your workforce, such as a developer or a technical analyst, to do the needful.

It is a time-consuming process, but it is a useful approach when working on smaller jobs and not abided by time.

  1. Ensure Consistency in Your Data Types

One of the marketing best practices for data consolidation is ensuring data type consistency before merging. Data from different sources might have a different format of illustration. For instance, one source might collect data in currency symbols, while the other platform might use currency abbreviations.

These discrepancies can be corrected at the root system before it is transferred to the unified database. Once the data is merged, it will be difficult for you to sort things out.

  1. Start with the Most Crucial Data

When approaching data consolidation, remember that it might be a complex task for big businesses with various audiences, marketing campaigns, and marketing channels. For such a setup, it will take a long time to attain all data, for which the crucial ones should be prioritized. Cross-channel and omnichannel marketing campaign data might be a good place to start.

Make Weavr Your One Stop Hub for Your Unified Data Analytics Needs

Weavr has an intuitive interface with crisp visualisations to help you bring all of your data under one roof and give you an insightful view of them. It is one of the perfect software solutions to help you with your data consolidation needs.

It can turn your collected marketing data into actionable insights to give you an idea of what to change, implement, and improve your business’s productivity. With Weavr Slate, setting up rightful marketing campaigns will be easier with seamless data consolidation.

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