The way we think about data is changing and companies need to rethink how they can approach consumer-centric data collection. Source Shutterstock

How embracing data analytics can help your startup thrive

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.

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Collecting, understanding and utilising 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.

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.

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.”