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Over the past years devops and sysadmins started shifting their #monitoringsucks mindset to #monitoringlove, pushing ahead in the game thanks to log data. But machine data analytics has most often been confined to IT purposes and other departments have overlooked these bits of information, sometimes unaware of its existence. But as our good ol’ friend Bob Dylan once said “Times they are a changin’ ”.

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Marketing services should now come to discover this new class of data. They can leverage new insights anchored deep in their services/products to quickly and precisely identify areas of improvement. More than checking monitoring performance and troubleshooting bugs, logs and machine data analytics are invaluable to shed light on usage and get clear marketing RUM. Teams can thus improve customer experience, marketing insights, and inform product development decisions.

Here comes 4 themes you can discuss with the team next door.

I. Increase customer retention

Customers do not like errors or latency, and could be left abandoning their shopping cart or leaving your app before taking any action… after all the efforts you went through to make them come to use your service! So data about server workloads, query response time, latency and usage patterns are critical.
By being granted access to machine data analytics, marketing teams can make sure that key sections or pages of their app, such as homepage or conversion funnel, are performing correctly. No more latency or errors to impact client acquisition or revenue.
For example, with log data you are able to create a dashboard that will let you monitor error pages on a website, correlating it to a specific country, server, device or user… thus entering the world of marketing RUM and answering questions like: what are the anonymized users encountering a bug? Are these users business critical to me? What is happening exactly? How long would it take us to fix their experience?
Remember the Internet Explorer 6 running joke? Every time an error came up, one would blame the usage of an unsupported browser like IE6. There was no time and no means to recreate the bug and quickly understand what had happened. Now you can actually know in seconds if this is the case, or not.
Machine data analytics will provide you with a new and fond understanding of your app performance and its impact on users. And teams will now be able to prioritize actions to fix bugs.

II. Optimizing the conversion process

Going one step further down the conversion process, those of you in the lead generation business will soon realise that log data can help you better monitor abandonment rate throughout your whole conversion funnel. Typical lead generation businesses would have a website sign up, followed by a final conversion somewhere else. Lead gen marketers often have much trouble getting final conversion data; if they are lucky, they would receive it in excel files one month later. With log data, you can directly monitor your final conversion completions and have a complete overview of your conversion process, saving a lot of precious time! Machine data analytics let you clearly see at what critical steps you are losing customers. You can then start taking actions on features/service to improve your final conversion rate.
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III. Drive informed marketing campaigns

With the incredible amount of new information contained within machine data, you can get completely new insights to more accurately target your marketing efforts.
Using data from the access logs, feature usage or product sales, you can identify patterns in purchasing behavior based on geographic regions and time of action. This information enables you to target specific items to specific customer sets based on the frequency that items are being viewed and purchased.
Take the example of a company renting media through an app or connected device. By getting direct information on renting patterns in specific cities or countries, marketing teams can now develop in store campaigns that fit in with local preferences, increasing relevance to potential customers!

IV. Inform Product/Service Decisions

Because machine data analytics can reflect the precise way products are being utilized, it’s a strategic part of the equation when a business is looking to expand services and plan their product roadmap. Log data shows you how and when features are used, so you should definitely have a look at what machine data is telling you. Discover that some features are barely used, others heavily utilized, while others still, are not used in the way you had envisioned. You don’t have to second guess what your clients think or do anymore. No more going through lengthy and expensive processes to get client feedback.
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At, releasing a feature goes in pair with actively monitoring its usage through log data. By following adoption rate and usage we make sure that all incremental efforts we do are in harmony with our clients’ interest. When we started providing a beta query API to our customers for easing the extraction of data and insights, we monitored its adoption rate growth, and looked at how customers were using it. So we are now working on the API version 1.0 directly focusing on what is important to our customers.

So, what are you waiting for? Get on top of this goldmine and let your marketing teams benefit from these new business insights through machine data analytics. Get some more insights on how alerting can help business teams or check how ADikteev business teams are using logs analytics.

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