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The Future of Omnichannel Marketing: Automated Data Collection and Analysis

Last updated: March 14, 2019

the-future-of-omnichannel-marketing-automated-data-collection-and-analysis

the-future-of-omnichannel-marketing-automated-data-collection-and-analysisOut of all of the digital marketing strategies available today, omnichannel marketing offers the most benefits. Omnichannel marketing is different from multichannel marketing in that it uses different channels to seamlessly funnel customers all toward one single goal (say, to buy a book or set a consultation appointment). Marketers across industries agree that omnichannel is indeed the future of marketing.

However, omnichannel marketing requires the precise measurement of campaign efforts across online and offline touchpoints as they work together to drive consumers down the funnel. That’s why the capability to automate big data collection and interpretation is so crucial, providing marketers with rapid, accurate and actionable insights for campaign optimization. Without proper data attribution, marketers are unable to best analyze and make decisions on what they see in the data itself. Below, we discuss some of the opportunities marketers have in data, as well as key focus areas to properly automate data collection so it can provide conclusive, useful results.

Marketing Opportunities in Big Data

Omnichannel marketing relies on big data to guide cross-channel optimization decisions. Without being able to see trends and patterns, marketers cannot plan and optimize their own campaigns. In today’s digital market, it becomes easy to be dazzled by the bells and whistles that many available data platforms claim to have, and the choices may seem simple. However, choosing what data to focus on should take time. It’s easy to get distracted with vanity data that isn’t actually explaining behavior that marketers can use to optimize campaigns.

While choosing what data to analyze takes time, once it’s set up, automated data should be available to help marketers rapidly make decisions while optimizing in-progress campaigns. For instance, if we use Google’s Keyword Planner on our PPC campaigns, we know that the data is pulling real-time recommended keywords based on search behavior. This allows us to optimize our campaigns accordingly.

While there are several different data sources available, few allow marketers to properly automate data collection. Being able to automatically receive data helps marketers cut down on analysis and interpretation time. What’s more, manually running reports or collecting data individually creates opportunities for user error, leading to data discrepancies that can drive improper analysis.

Any automation that’s available should be utilized when it is helpful for the campaign. One such area of automation that is becoming more common in marketing data is artificial intelligence (AI).

Establish Data Sources

Whether or not AI is available, the key first step in setting up an omnichannel marketing analysis is to establish key data sources of focus. Where are all the platforms that customers may be seeing your marketing messages or campaign collateral? This could include:

  • TV

  • Radio

  • Mobile Apps or Alerts

  • Paid Search

  • Organic Social Media Content

  • Website Features

  • Influencer Campaigns

  • External Press Coverage

  • Paid Social Media

  • Media: YouTube videos, podcasts, etc

The best data analytics and collection platforms are ones that intelligently use an organization’s own user data with big data sources and trends. Once each channel is outlined, it’s time to outline how a user will use that channel to reach the single goal we’ve set for the campaign. For instance, if the goal is to sign up for a webinar, we can use unified link tracking across all platforms to determine sources of traffic in analytics. From there, the data  taken from this action on each platform can be properly set up and automated.

Establish Modeling and Attribution

Having the correct data attribution and modeling is key for optimizing a marketing campaign. Without all data channels working together with the correct attribution, the ability to have multiple channels of data is completely useless. Only when marketers have data that is being categorized and displayed properly are they able to make good decisions about their campaigns and customers’ expectations.

Data sources are getting smarter about attribution and even automating it for marketers. For instance, data-driven attribution in Google Analytics notes that a customer may interact or see your brand’s messaging across several platforms. It properly gives credit to each channel that helped a user eventually convert. Prioritize using data collection tools that use automated means of proper attribution.

Continuously Improve Data Quality

A marketer’s insights are only as good as their data. Be sure that all data is as accurate as possible. Use data checking and validation when possible to cross-reference data against available databases OR have an outside team or other employee run their own data analysis to verify the original data setup is correct.

Don’t get lazy with data collection. Just because it is automated, it doesn’t mean discrepancies won’t continue to pop up.

Final Thoughts

As new technologies improve and user behavior continues to change, outdated data collection modeling isn’t going to help, and will more likely hurt marketing efforts. Improving automated data procedures, attribution and sources is  the best way for marketers to fully utilize all the benefits of big data collection and analysis for omnichannel campaigns.

Written by Marketing Evolution