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And since most of us are fans and students of his book Web Analytics: An Hour a Day (I include myself in both of these categories) we do not take issue with this idea; also we do not take issue with it because his book is so chock full of pearls of wisdom that everyone gleans some insights from it regardless of their level of experience.
However I want to open up for discussion on how working with real time raw data can be cost effective. And, it can provide greater ROI if and only if the analytics product´s surrounding eco-system is set up in a way that enables the data to be leveraged effectively. In fact, my theory is that:
• Real Time Data Can be Leveraged Effectively
• Both Real Time and Raw Data have Beneficial Repercussions throughout every Analysis
• Both Real Time and Raw Data Create Actionable Metrics
• Real Time Raw Data Ensures Greater Accuracy (no caching) and Timeliness
• Real Time Raw Data Future-Proofs Your Analytics Solution
I absolutely agree with Avinash Kaushik that real-time data does not matter to a company unless they will actually take action on the reports; that is what in the long run drives the ROI of the tool.
In general however the ROI on any analytics tool will be greater if each person on every team that touches the website has the power and the understanding to create little frequent changes; i.e the power of crowd-sourcing for managing a large, dispersed multi-national website is immensely greater than having one smart analyst in one location interpreting all the data. No matter how smart they are, one analyst can never react in a timely enough manner, nor in a localized enough manner, nor even be able to digest all the complex statistics fast enough to glean the insights that create the actions that drive the ROI.
Therefore, if each person on each team can react daily to even just one real time data point, you will be creating a competitive advantage over those that have one analyst in a lagged time frame. The actions will be created by those that are familiar with the data and in a time frame that provides real monetary value (think of the rapid changes that create additional revenue in eCommerce, Travel, News Content, etc.)
Therefore the tool you choose needs to complement the real time data with an easy to use interface and unique user management so that each marketing person can have the metrics that matter to them provided to them on a daily basis. If each person is responsible for certain KPIs (Key Performance Indicators) and the tool provides an intuitive enough interface or an export capability so that these people will potentially not even have to learn how to use the tool, then you have a winning combination. Real time data with unique user management and easy to understand reporting is very effective and can drive the ROI required. However, you have to have the complete eco-system in one tool and at a reasonable price point in order to make implementing it worthwhile.
And, even more importantly, I would agree with Avinash that you need to also ask yourself whether your website gets enough visitors exhibiting the right behavior to ensure that the real time data choices you make will result in statistically significant outcomes. He does confirm that “..statistical significance is not just about raw numbers..” but more about the impact of the changes you can make in real time. However, if it is clear that your business can impact the ROI by leveraging real time data, then you should also be looking for a tool that can handle significant volumes of data in real time with ease (i.e. as much as 1B page impressions a month) If you have a large amount of data that you are processing then even smaller changes you make can have quite a large monetary impact.
The same idea is pervasive about leveraging raw data for analytics – i.e. it might be great in theory, but provides poor ROI because it is too costly.
However, having the raw data enables complete flexibility in every analysis, as well as future proofs your analytics solution – increasing the tools´ long term value and again providing more effective ROI.
When all data can be correlated in any way in all time periods, this enables much more detailed views, segmentation, and most importantly, retro-active on-the-fly queries. In other tools you need to know ahead of time what sort of analysis you think will be important in the future; with the raw data you can slice and dice the data any way you would like at any moment. You can add any special unique metrics in any time frame. Therefore leveraging raw data becomes imperative as you compare and contrast different campaign success metrics in different time periods ( Even Avinash Kaushik cites that as your “..strategic objectives evolve [y]ou should expect a 20% churn in your main KPIs every six months…if they are not changing at least that much, either not a single dimension of your business has changed on the Web in that time (highly unlikely) or your KPI’s are stale.. ” p.349.)
In addition, raw data´s ability to provide a granular enough view so that you will get user level data also makes the ROI on the tool much higher than those tools giving you aggregated information. Who wouldn´t want to receive a timely email with a special discount coupon for a pair of pants that you had just put in your shopping cart but then abandoned because they were too expensive?
Thus, the level of detail that raw data provides creates action oriented metrics – not vanity metrics. For example, knowing that your conversion rate is increasing is great and makes a website owner proud (vanity metrics) but what are the next steps that one should take to continue to help increase this traffic? High conversion rates could be the result of non-reproduce- able actions, such as moving out a deeply discounted product line. With a raw data based analytics solution, you can drill down to find out exactly how this conversion rate was increased and by which visitor segments on which search engines, thus enabling the online marketer to know exactly what action to take next ( buy more keywords on certain search engines, reach out to certain publishers, etc.)
Thus, granular, extensive, sophisticated data analysis along with the ability to perform any retro-active analysis on the fly is the key to providing better ROI and getting longer term value from your analytics tool.
In sum, real-time raw data can be cost effective if the attributes of the tool enable your team to leverage action-oriented metrics now and any unknown metrics that they may want to leverage in the future at a reasonable price point.
Cecily Robyn Lough is currently Director of International Sales at Webtrekk GmbH in Berlin. She believes that Webtrekk´s current analytics solution does have the ability to make raw, real-time data cost effective for web sites that need up to a billion pieces of data segmented on-the-fly.
Please contact her at Cecily@webtrekk.com or +49 (0) 30 755 415 440 for more information
