Why NOT CONNECTING your Analytics can be hugely detrimental to your business

Collecting data for offline analysis at your leisure or convenience used to be good enough. Not anymore. With the number of IoT connected devices exploding, businesses must connect their data with real-time analysis to stay competitive in today’s markets.

The world is different now – Technology is everywhere

In 2017 there were over 8.4 Billion – yes, billion – IoT connected devices on the planet, superseding the 7.48 Billion people in the world. (1) What this means for your brand and your products is that you need to approach data analysis in a completely different way.

To detect situations about to spiral out of control, or to capitalize on real-time opportunities in real-time, you need to work with data in – you guessed it – real-time. To remain competitive and keep customers happy, it’s becoming increasingly critical that you directly connect your analytics platform to your data systems. and work with those data streams in real-time.

Experience is everything – New data, new rules

In 2019, the enterprise IoT sector alone will be larger than the combined smartphone and tablet market. (2) That means a lot of real-time data will be generated, all of which will need to be analyzed.  Just have a look at the following image, which shows the amount of data created in just 60 seconds in 2017.

This, in no way, suggests that the traditional offline analysis of data will not continue to be important. Companies will still need to analyze historical trends (for example), so that traditional, deep-dive, strategic analysis will remain.  But brands can no longer rely solely on historical collections of data and information.

It cannot be overstated that, for businesses today, the real value of data analysis, is in real-time. Given the massive volumes of data now prevalent, companies need to figure out what is happening on-the-fly. You cannot afford to wait.

An important point to note here is that companies should not look to completely replace their collection of data with connections to systems. One activity does not negate the other. Instead, they must look to connect as many sources or ‘sensor’ systems as possible, increasing the velocity and the visibility of their analytical scope, enabling a 360° view.  Additionally, there will always be cases where systems cannot be connected (for a multitude of reasons), but there is still unquestionable value in analyzing the historical trending data from these unconnected systems.

Real-Time decision making

Create value where others don’t expect to find it

Real-Time choices make your customers happy. Really happy.

A major goal of real-time analytics in Customer Relationship Management is to service customer requests as quickly as possible, while ensuring a robust decision-making process and feedback mechanism. Additionally, enabling customer interaction in real-time, at ‘moments of truth’, is highly likely to lead to great customer satisfaction.

A leading UK courier company excels in this area by using Analytics to determine the best options for their customers, coupled with real-time workflows that drive great customer satisfaction.

At the heart of this company’s successes in the past year is its end-customer app. The technology allows customers to personalize their delivery experience by changing their preferences in the application in real time. Customers can see real-time where the delivery driver is on a map and where they are in the driver’s queue.

Snooze and you lose. Connect to win.

Real-Time data can also be used to lift sales.  Usage of data in real-time must be balanced with providing the right information, at the right time, and within the right context, enabling you to deliver personalized offers that make sense.

A large global credit card provider was struggling to maximize cross-sell and upsell revenue on customer activation calls. Agents often defaulted to the easiest option to sell products, and there was no systematic way for them to determine the best offer for the customer. The provider started leveraging real-time information from live conversations between agents and customers, married that to their analytics model based on historical purchases, and then delivered the results to a real-time agent desktop application. This enabled agents to deliver optimal, personalized product offers to live customers, which not only resulted in more sales per call, but bigger ticket sizes per sale, thereby increasing revenue by an impressive 20%.

Think differently – Make business better

With the explosion of data being generated as a result of the plethora of devices being used today – devices that are becoming increasingly connected to each other – it is imperative that analytics keep pace and anticipate tomorrow’s realities. Analytics can no longer afford to be based on historical data. The need of the hour is for companies to connect the various sources from which this data is being generated, and then connect them to their analytics platforms. Companies that fail to do this will suffer from a lack of understanding of the individual needs of their customers, and will struggle to remain relevant in a competitive and disruptive marketplace.

By Kester  Fernando, Strategic Asset Area Manager  (Analytics & Social)

Key Sources

  1. Market Pulse Report Internet of Things (IOT), UK, discover key trends and insights on disruptive technologies and IOT innovations by GrowthEnabler 2017
  2. http://uk.businessinsider.com/the-enterprise-internet-of-things-market-2014-12?r=US&IR=T
  3. https://www.webtrends.com/blog/2016/08/why-real-time-data-will-become-essential-to-marketing/
  4. http://www.digitalistmag.com/technologies/analytics/2013/06/25/three-reasons-your-company-needs-real-time-analytics-092400
  5. http://www.computerweekly.com/opinion/Why-real-time-CRM-analytics-is-hot
  6. http://searchbusinessanalytics.techtarget.com/essentialguide/IoT-analytics-guide-Understanding-Internet-of-Things-data
  7. https://www.softwareadvice.com/resources/iot-data-analytics-use-cases/
  8. https://www.accenture.com/in-en/internet-of-things-analytics
  9. https://www.dpd.co.uk/content/about_dpd/awards.jsp
  10. http://www.oracle.com/us/technologies/big-data/six-patterns-big-data-infographic-2956541.pdf
  11. http://go.logianalytics.com/rs/793-ECD-841/images/State-of-Analytics-Adoption-Report%20-%20final-min.pdf
  12. http://businessoverbroadway.com/state-of-analytics-in-customer-programs-customer-loyalty-focus-machine-learning-adoption-and-the-data-science-skill-gap

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