Data analytics: Tips to boost your company’s strike rate

Companies today are successful because they’re able to capture the right data and can make sense of it quickly and in-time for managers to make the right decisions.

According to a Forrester report, although 74 percent of firms say they want to be “data-driven”, only 29 percent are able to claim they are good at connecting analytics to action – and that’s the problem.

Everyone has access to data – either on their own or through their partners, but it’s how they use it that makes all the difference in the world. Amazon at home and Alibaba far away in the East are great examples of how data can catapult your business far ahead of your competitors.

Amazon is the global leader in e-commerce – but it didn’t spring onto the internet as the market leader. Data analytics played a big role in its rise.

Part of Amazon’s success lies in its attitude to collecting and understanding data, then using this information to create pioneering strategies.

Similarly, Asian e-commerce giant Alibaba operates TaoBao, a multi-billion-dollar, B2B marketplace.

By using software such as GraphX and Apache 9.0, Alibaba can collate the first-hand data it receives from its online users, and use it to enhance marketing campaigns and create a better experience for users.

Collecting, understanding and utilizing data is crucial not only for the giants of e-commerce but also smaller companies and startups.

According to a survey conducted by Interana, 88 percent of companies reported that while they understood the value of data, most admitted they struggle to implement accurate, agile analytics.

As daunting as the world of analytics may appear, there are helpful methods and platforms for startups to use. StackList offers an up-to-date source of some of the most helpful and kindly priced analytic tools.

However, understanding what to do with the information holds the key to Amazon-like success.

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— Allied for Startups (@Allied4Startups) September 26, 2017

Knowing which data is most effective

The best way to understanding your demographic is through first-hand data. This is usually collated through cookie software. Startups can also share first-hand data through a data onboarder like LiveRamp.

Used correctly, you can then target your audience with personal and relevant adverts.

Make reading the data easy for yourself

Don’t have data in every corner of the Internet. To make analysis less time-consuming, pull all the first, second, and third-party data together. Your marketing team will thank you and you will see a more thorough study of the analytics.

Measure data that matters

Trim away the excess of unhelpful data. There is no such thing as bad data, but data that clearly sits outside of Key Performance Indicators (KPIs), such as sales and SEO metrics, will waste your time and slow down the process.

5 Myths of Big Data 🔮#Infographic #BigData #DataScience #MachineLearning #ML #Business #DataAnalytics #Analytics #AI #IoT #Industry40 pic.twitter.com/F8AvKIp3YJ

— Matt Reaney (@mattreaney_) September 28, 2017

Don’t take it personally

It is important to hypothesize your data before analysis. But ensure your hypothesis is based on literature and past data. Otherwise you risk wasting time frantically explaining something that could be a random error.

Similarly, if it is a concerning anomaly that stands outside your business strategy, don’t take it personally.

Data will not always show you what you want to see, and sometimes it won’t be wholly significant, but with every analysis of your data, you are closer to perfecting your business-customer relationship.

The relevance of data analytics is crucial to every business, and as Jeff Bezos, founder and CEO of Amazon, explains: “If you’re competitor-focused, you must wait until there is a competitor doing something. Being customer-focused allows you to be pioneering.”