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Is real time analytics really that important?

Analytics
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8 minutes for reading

Real time analytics

More and more analysts and companies are looking for analytics solutions that can provide data in real time, the famous real time analytics. They condition the hiring and use of tools only if they offer reports in real time.

In this article I will show you why real-time analysis is overestimated. I will also give you tips to know when your company will be ready to use them and get results from them.

Because real-time analytics are not relevant

Anyone who knows me knows that I'm not a big fan of real time analytics. It is obviously not for this reason that real-time analysis is not important. At least not for most companies.

Reasons why I don't consider real-time analytics to be so relevant:

More reports and less analysis

In the universe of web analytics we already have so much data to analyze that real-time data only makes things worse. Not that I'm being lazy, but analyzing a large volume of data and having insights that bring value to the business in real time is not as simple as it sounds.

First, any analyst who brings more than one insight per week to your business is deceiving you. No one will be able to bring relevant and valuable information to your business every week. It takes analysis and good judgment.

Second, reporting is not analyzing and have insights. Real-time analysis tools offer several types of reports, but few (or almost none) offer some insight that can turn into results.

A lot of investment in tools and little in people

The search for real time analytics makes companies wrongly hire tools and professionals. A good analyst can bring valuable information to his decision making using only free tools, such as Google Analytics, for example.

Most of the time, companies take the opposite path, hiring robust tools such as Chartbeat and Piano and delegating an analysis of the received data to an intern. The chances of having good analyzes are very low.

On the other hand, a good professional is able to extract as many free tools at a much lower cost.

Read too: "Analytics tools: 5 reasons not to use them

Greater complexity in systems and processes

This is a point that most companies are not aware of. Capturing and processing all data in real time requires much more complex and robust structure and processes.

The collection, processing and storage of this data requires a much larger and better structured infrastructure.

Wrong but safe decision making

The terrible false notion of trust.

Many think that having the data in real time will make them more prepared for the competition. This is not always true as it can be quite the opposite.

Companies are unaware of the real cost involved in being able to work with real-time data and return on investment.

So far we've seen reasons why I don't think real-time analytics are so important. However, it does not mean that you can never benefit from real-time data.

If you think your company is ready to analyze real-time data, see if it meets the following items.

When real time analytics is recommended

Statistical significance

Do you get enough visitors that a real-time analysis can accurately represent the behavior of a segment? Does your site have enough conversions in real time for action to be taken?

If you have 100 visitors a day on your site and 2 conversions, real time is probably not a good fit for your analytics strategy.

It does not mean that it needs thousands or millions of visitors to the site, but it does need at least a significant number of visitors with expected behavior that can be used for analysis.

Analytical ability

To analyze data in real time you need to have at least one full time analyst on the team who has good analytical skills.

A professional with good analytical skills will be able to distinguish relevant information from noise. I work with publishers who delegate real time to editors and editors who are unaware of business metrics and KPIs and therefore end up making the wrong decisions.

Read too: "Digital Marketing Metrics: Which Are Important?

Decentralized decision making

If a company wants to adopt real time analytics it needs to empower your employees and decentralize decision-making. Real time is now. Not tomorrow or a week from now using real-time data from days ago.

Suppose your hierarchical structure requires that you receive data in real time, then inform your superior, who then reports to the supervisor who, in agreement, sends it to the CxO to make a decision. What good is real time data if your suggestion to pause a PPC campaign will take 3 days to happen?

Operational execution capacity

You have identified a point of improvement, a banner or a block on the cover of your website, and you want to change it immediately considering that the real time has indicated that it can be improved. Do these campaign and site changes take two or three days to occur? Most likely, real time is not necessary in your company.

If you can't change a campaign ad or banner on your site in minutes, real time is not for you.

“Data at the right time, not in real time”

As I mentioned earlier, if your decision making takes days, there is no point in investing in real time.

Here is a very common flow: data in real time is analyzed (about 2-3 hours) and presented to the superior (1 hour) who in turn sends it to a decision-making committee (1 day). The committee queues and analyzes priorities (2 weeks), questions the numbers (1 week) and only then sends it to the decision maker. This in turn identifies that the decision should have been made 3 weeks ago and makes a decision based on your instinct in 5 seconds.

Got it ?!

Do the math. Did real-time data have any value for the organization?

Almost all large companies have a complex and often cast structure, being unable to react in real time. If you can't react in real time, why do you need real-time data?

A good analyst will know the right time to present data and insights in the organization.

Focus your efforts on important and strategic things. Real-time analytics is very expensive!

Avinash Kaushik proposes a way to check if you really need data in real time:

Does a human have to be involved from receiving data to making a decision? If the answer is yes, then you don't need real-time data, you need data on time. If the answer is no (say you have automated intelligence / rules systems), then you need real-time data.

If your company can meet all of the above requirements, it is possible that real-time data can make a difference. Otherwise, invest in people and improve the analysis and decision-making process.

Concluding

Real-time analytics are not relevant for the following reasons:

  • generate many reports and few analyzes;
  • a lot of investment in tools and little in people;
  • increase complexity in systems and processes;
  • lead to a false sense of trust.

Real time analytics is recommended if:

  • there is statistical significance;
  • it has professionals with good analytical skills;
  • the team is empowered (decentralized);
  • operational execution capacity exists;
  • decisions are made quickly.

And in your company, are you all hungry for real time analytics?

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