Digital Marketing Attribution: 2 Examples of Tapping the Data Disruption
You’ve likely heard something about “big data,” and may be wondering what this is and if it has any impact on marketers and your world. There are lots of ways people use (and misuse) the term, but for purposes of this column, let’s day that Big Data is data that has the three “V” qualities:
- Volume. There is a LOT of it.
- Velocity. It is created, transmitted and received at a very fast rate – like in real time data sourcing.
- Variety. It is multi structured (not linear or easily aligned to a structured database format) and sourced from multiple customer interactions. This might include clickstream (website visits), behavioral insights, email and SMS response data, social posts and tweets and search keyword activity.
In essence, big data disrupts marketing. It upsets the normal “container” of marketing data, because the unstructured and multi structured formats don’t match the kinds of one-to-one relationship of data element with database field (the way that structured data works). It upsets the CRM paradigm because it’s fluid, hard to sort and prioritize and not always attributable to a specific person. It also disrupts the infrastructure cap ex budget – big data is just that: Big.
Do not be afraid. Gartner has reported that competitive advantage goes to those who tap into this disruption of data. There are plenty of opportunities that involve harnessing big data and making sense of it. At one level, it’s important to just ask questions of the data. You can only make better decisions if you utilize the gems hidden in your vast data storehouses. Better, imagine what you could do if you could use all the data you have. And I mean: All. The. Data. That is pretty exciting. You’d be doing things like social community relationship analysis, persona-based segmentations, behavioral modeling, path to purchase analysis, real time offer management, multi touch attribution analysis, advertising and media analysis, and more.
Truthfully, it’s an incredible opportunity, but it can be a frustrating challenge to get your arms around. Especially when you consider that any use of data also impacts the relationship you have with your customers and prospects. There can be a fine line between cool and creepy.
One area where marketers are optimizing their investments in big data analysis is in the area of digital marketing attribution, which is itself the first step to digital marketing optimization. Most attribution today is last click, more for the complexity in managing data than from marketer choice. But now that we are tapping big data, attribution analysis can track behavioral insights and better understand and serve customers who are interacting across an expanding universe of multiple channels, touchpoints, and data sources – everything from email to search, digital advertising, websites and social media.
The volume and complexity of new data sources require advanced analytics beyond ‘last touch’ or ‘last click’ attribution. To make accurate budgeting decisions, marketers need to take into account multi-channel, multi-touch purchasing cycles. Consider two examples of how attribution could work for you:
- A major online and offline retailer leverages ‘big data’ to derive consumer insights that are deployed across channels. Instead of relying on sampling, customer intelligence is created from big data analysis. Customers benefit from more personalized experiences.
- An online only retailer ties together click stream information with email logs, ad viewing information, and operational information in order identify customer preferences and behavior – and how to optimize marketing spend. This includes parsing of Twitter feeds and sentiment analysis.
Responsible data-driven marketers must think differently. Our customers expect it, and our markets demand it. Use this kind of early application of big data to improve your attribution models, and gain visibility into marketing activity to optimize the use of new channels and deliver remarkable customer experience across conversation points.
What is your story around attribution? Are you on a path to tap the disruption of data or are you sticking with last click attribution models? Share with us your learnings below.
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