Businesses and agencies struggle with managing their data. Whether they are marketing through different channels or handling multiple clients, their data is often siloed across various platforms.
Because of these data silos, they find themselves unable to understand their data well enough to fully grasp the performance of their marketing efforts. That's why consolidating and managing marketing data has become crucial for many businesses and marketers.
If you’re running marketing campaigns on platforms like Facebook, Instagram, and TikTok, you need to consolidate your marketing data.
Marketing data consolidation involves combining data from various sources to create a single, consistent view. By bringing together different pieces of marketing data, you can better understand customer preferences and behavior. This approach allows businesses to use predictive insights, connect more closely with customers, anticipate their actions, and identify new business opportunities.
By employing the right data science methodologies, an organization can be better equipped to consolidate their data to measure their marketing efforts - but only if there’s a firm connection between what the analytics can deliver and what the business is trying to accomplish. In essence, what is the problem you are trying to solve and how you can use the collected data to answer it?
Pro tip: Looking for a reliable partner to offer a top-notch data consolidation solution? Connect with Data Pilot for a free consultation!
Data consolidation involves the integration, harmonization, and centralization of data from multiple disparate sources into a single, unified dataset or repository.
In many organizations, data often resides in isolated pockets or silos, hindering accessibility and usability. Through the process of extracting, transforming, and loading (ETL), data consolidation ensures data is accurate, reliable, and aligned with the organization's business goals. This unification breaks down silos, enabling organizations to manage data effectively and unlock the full potential of their information assets.
Data consolidation enables marketing departments to:
As a marketer, referring to all the data you’re getting is wise. But at the same time, having the right practices and tools to make sense of this marketing data can ensure you enjoy its benefits.
Many businesses, such as retailers, healthcare providers, and banks, are creating 360-degree views of their customers. This comprehensive representation of data helps them gain valuable insights and benefits.
Sephora, a major player in the cosmetic beauty retail industry with both physical stores and an innovative online presence, has been using AI and data analytics since 2013 to understand consumer behavior.
Source: Sephora
This approach has helped them enhance their marketing strategies, increase market share, delight customers, and build loyalty. By collecting customer data, they can predict preferences and offer personalized product recommendations. Using the Google Analytics 360 suite, Sephora's analytics team identified which online ads led to in-store purchases, resulting in a threefold increase in sales from digital advertising.
Under Armour, a sportswear giant, has ramped up daily engagement with consumers through mobile apps. Acquiring fitness leaders like MapMyRun, Endomondo, and MyFitnessPal, they built a massive digital ecosystem – boasting the world's largest online fitness community of 200 million. This data empowers them to deliver targeted marketing based on users' fitness journeys.
Source: Under Armour
A while back, Orlando Magic increased its fan engagement with its mobile app data and machine learning. This NBA team, once reliant on basic marketing analytics for ticket sales, now personalizes campaigns and analyzes game data with app insights. This strategy boosted attendance, with 100% season ticket holder app usage and a 20% jump in fan satisfaction with arena tech.
Source: NBA
Data Pilot has helped brands build a robust marketing data infrastructure and leverage it for better decision-making across several industries like retail and e-commerce, fashion and textile, media and advertisement, and food and beverages.
Source: Data Pilot Marketing Analytics Dashboard
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