What is Big Data?

Everyone’s talking about Big Data: who’s got it, who are the experts on it, and who can make digital marketing more successful with it. But what is it exactly?

Big Data refers to the massive collection of consumer information from various offline and online sources that can be analyzed to reveal patterns, trends, and behaviors of people and incorporated into data-driven marketing strategies.

Why Does Big Data Matter?

Big Data functions on the principle that the more you know about people and understand their behaviors, the more you can accurately predict what they will do in the future.

In other words, it’s not about the amount of data that matters. Rather, it’s what companies do with the data that brings real value to the table.

Today’s leading marketers implement these data insights to better understand, predict, and deliver experiences fit to customers’ ever-changing interests, needs, and preferences. This drives the practice of data-driven marketing, where real audience insights about consumers are analyzed to build smarter, action-based marketing strategies and campaigns.

However, Big Data can become complicated and overwhelming without the right approach and the appropriate technology to analyze all of the data points.

Traditionally, Big Data was assessed by the Three V’s:

  1. Volume – The amount of data flowing through an organization, typically merged by technologies to host a variety of sources
  2. Velocity – The speed of information generated and flowing into the enterprise; the closer to real-time, the better
  3. Variety – The types of data available, from structured to unstructured, offline to online, etc.

According to SAS, Big Data must also be evaluated by variability (daily, seasonal, and event-triggered data loads) and complexity (the challenge of linking different sources of data and cleaning and transforming it across systems).

How to Optimize Data-Driven Audiences

One of the most important and valuable ways to utilize data is to better understand your audiences, aka getting to know the actual people you’re marketing to.

We’ve provided 3 tips on how to interpret and use Big Data to optimize data-driven target audiences:

1. Combine data sources for a full view of consumers.

Today’s consumers are connected on an average of 3 or more devices, which means more data sources are necessary to keep up with them. It also means that there is that much more potential for insights into how people are engaging.

In order to gain a comprehensive view of consumers across all channels, marketers must invest in the linkage of Big Data.

By merging offline, online, and mobile sources, typically managed through a Data Management Platform (DMP), you can understand individuals on a deeper level.

Target your audience based on:

  • Offline data – demographic, geographic, postal address, purchase behaviors
  • Online data – cookie data, online browsing, email address
  • Mobile data – device ID, app downloads, app usage

big dataFor example, let’s say a major retail department store is looking for the right audience to reach during the holiday season to drive in-store sales. By merging offline, online and mobile data, we are able to identify the best group of individuals for a holiday campaign.

Big Data allows us to hyper-target a custom audience of women who are between the ages of 30 and 55 and have children in their household, a household income of $50K or more, express an interest in holiday/bargain shopping, and love to use shopping apps and browse outfits online.

By delivering ads to the right audience, you are reaching people who are most likely to be interested in your business – driving engagement across all channels and lowering overall customer acquisition costs.

2. Listen actively to how people engage.

Once identifying the right target audience, you can deliver media to them across multiple channels. It’s essential to observe through real-time data how consumers engage across various channels and devices to analyze where they are most likely to convert.

Track cross-channel activity through pixels linked to mobile device IDs for a true one-to-one understanding of the person behind the screen.

big data

Gain insights into your original audience, identify who’s engaging where, and optimize new audiences and media strategies to further increase engagement and drive campaign success.

3. Apply audience insights to drive smarter strategy.

A full database of consumer information that’s analyzed from start to finish of a campaign allows for true insights that can reveal smarter, more efficient marketing strategies.

  • Audience optimization – Whether it’s discovering new insights about your current audience, finding new lookalike audiences who resemble your best customers, or adjusting your marketing strategy to exclude unengaged consumers, audience optimization utilizes Big Data insights to make sure you’re reaching the right people.
  • Improved media strategy – By understanding where your target audience is engaging most, you can deliver ads across their favorite media platforms to drive engagement and lower overall customer acquisition costs.
  • Measurable results – With Big Data, you can access insights into how your consumers are responding to your digital campaigns in terms of Point-of-Sale Matchback (how many of them actually come to the store and purchase from your business), click-through rates, and conversion rates. Ensure no marketing dollar is wasted with real, measurable results to continuously improve future campaigns.

Most importantly, Big Data provides real insights into who people are. The more marketers can understand, interpret, and analyze about consumers, the more leverage they have to deliver personalized, valuable campaigns to the right people, in the right place, at the right time.

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Jessica Malooley

Author Jessica Malooley

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