Virtually every piece of software I get pitched puts near to or real time analytics at my fingertips 24/7/365. It sounds fantastic and in some cases, is true – but the reality of ‘real time’ data is that very few products actually deliver data in real time due to the need to process raw data or dependency on other not-so-real-time technologies.

But, this article is not about whether or not real time data actually comes in real time – what’s more important the than latency of delivery is the accuracy and subsequent value of real time versus aggregated data sets.

In order to understand the time and place for real time versus aggregated data, it’s worth taking a step back to understand why Web analytics haven’t always come in real time. A common practice in analytics software is to have two types of databases (note: this is simplified but directionally accurate) – one containing raw data and another with aggregated data.

While new performance data pours into the raw database in batches, the raw data is cleaned up and populated into the aggregated database, which can then be queried against – populating performance data in the software UI. Streamlining the flow of data in and out of the raw database keeps performance stable and mitigates the likelihood of major issues stemming from too many queries stalling the raw database.

In order to provide real time data, you need to remove the aggregation process and have enough bandwidth and processing power to churn through new data as fast as possible while managing the demand to query against the raw database.

As a result, it’s understandably very expensive to maintain and scale true real time analytics without succumbing to heavy data sampling or limiting the types or queries against the database to mitigate risk of an epic failure.

Google Analytics (the free, non-premium, version; which does heavy data sampling), is a perfect example of a horrible real time dashboard. Sampling incomplete data never leads to accurate KPIs – it usually takes about 24 hours to get the data right in GA.

What Are The Benefits Of Real Time Analytics?

It’s perfect for the VP of Sales to watch revenue coming rolling in, constantly refreshing the internal dashboard to see if tonight will bring tequila shots of victory or preparation for a meeting with the CEO to figure out what’s going wrong. I used to have a dashboard like that…and I can confidently say that nothing productive came from anyone constantly refreshing the screen.

The dangers over overreacting to real time analytics are highlighted by the instinct to make significant changes to marketing campaigns using insight from real time intra-day data. If daily revenue is lagging, it’s easy to overreact by bidding down on paid search display ads as a means of maintaining hitting ad cost goals.

 

This can lead to a downward spiral because most ad servers are not designed to report and be managed in real time. The analytics behind performance marketing are built on statistically significant data sets leading to a logical decision making process.

The experienced analysts knows that patterns and trend lines are not made in real time. Understanding the value of a visit to your website on a Monday at 4 pm takes thousands and thousands of similar visits aggregated and normalized to provide an average value.

Creating projections modeling accurate historical trend lines, while not nearly as sexy as the ‘Real Time Dashboard’, are more reliable and can predict within acceptable variance for the purposes of a projection – leaving little to assumptions and chance.

As performance marketers, we are not in the business of rash decisions. We thrive on statistically significant data sets and the knowledge that acting rash on incomplete data could have detrimental effects on the marketing program. We take good days and bad days in stride knowing that if we make the right decisions there will be more good than bad, we’ll hit our numbers, and life will be good.

So while the bossman is freaking out that the numbers look soft because his real time dashboard says so, you head out to happy hour knowing that tomorrow morning, it’ll be all good.

Opinions expressed in the article are those of the guest author and not necessarily Search Engine Land.

Related Topics: Channel: Analytics | Search & Analytics

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About The Author: is in charge of client strategy at Fusion Tree, a performance marketing and analytics consulting group, and is based in the San Francisco bay area.

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  • http://twitter.com/antoinegay Antoine Gay

    Analytics platform are supposed to offer to track everything, from campaign (utm in GA) to content, onsite ads and conversions/orders, and if it is already tracked by an Adserver or other tool, it has to be double tracked with the Analytics tool.
    Most professional tools are going away from real time, and some like Chartbeat will give you info at a T time. AT Internet provides all metrics in real time, few minutes after, and APIs allow to export this. Dashboards in a News room are the most frequent example of real time analytics usage.

  • http://www.rimmkaufman.com/ George Michie

    Great post, Benny.  As is often the case:  that which sounds sexy and amazing turns out to be ugly and unhealthy when it comes to practical use.

  • http://borasky-research.net/about-data-journalism-developer-studio-pricing-survey/ M. Edward (Ed) Borasky

    Real-time marketing may be primitive now, but at some point it’s going to be a competitive advantage to have it. It’s just like finance – for traders, it’s now a competitive advantage to have your servers close to those that power the exchanges where you trade, and to have algorithms that understand market microstructure.

    I can’t predict the growth rates – I don’t have any data – but I’m betting that real-time marketing, especially in mobile, *will* grow and those who ignore its potential will be left behind. Facebook and Twitter are well-positioned to make it happen.

  • http://twitter.com/JeffreyRusso Jeffrey Russo

    Couldn’t agree more – real time analytics sounds sexy, and it’s an easy feature to market (“think of what you could be missing during that 4 hour lag!”) But aside from a few very specific situations, I’d really question how much most marketers get out of real time data. Correct analysis is best done on statistically significant sets of data after the dust has settled. 

    All technical limitations aside, knowing how many people are on your site, or exactly what your visitor count and distribution is at any given moment in time appeals to our obsessive nature, but doesn’t really offer much value in analysis.

  • http://twitter.com/CollinTate CollinTate

    Great article Benny. 

    For me, I’ve found that the only scenarios in which real time analytics are actually useful is during a product launch or sales event. Real time analytics allow me to recognize sales bottlenecks that were not identified during planning or pre-launch and catch issues that cause visitors to abandon at a high rate. Using real time data, I can make improvements on the fly. 

    Am I the only one who got the Chappelle’s Show reference? Nice one Benny!

  • http://twitter.com/bennyblum Benny Blum

    Thanks, @CollinTate:twitter . Glad somebody caught the reference. The original title was ‘When Keeping it Real Time Goes Wrong’ :)

  • http://twitter.com/Winooski Nato (Nate Orshan)

    There’s actually one context in which real-time analytics are extremely useful: In enterprise settings where either a significant campaign has just gone live or where a significant site code change has just gone live.

    I’ve seen myself how access to real-time analytics helped determine that there were site problems (due to a spike in traffic) and helped the company get IT resources on the issue immediately. Absent those analytics, it’s possible much of the extra traffic in that case would have been wasted on a slow, malfunctioning site; as it was, the engineers were able to save the day. 

    This is a slightly different scenario than Mr. Blum describes, where access to real-time analytics helps thwart a marketing campaign, and it probably only starts being viable when an organization is of significant size, but it bears sharing! 

 

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