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Six ways to take your big data capabilities from beginner to intermediate

Technology & Data

Six ways to take your big data capabilities from beginner to intermediate


updated 29/01/16 : details of FT paywall

Deeps De Silva outlines how marketers and organisations can use big data to effectively target consumers and plan, automate and breed online sales.

Deeps de Silva Headshot 180A fascinating paper came out in 2015 on ‘harbingers of failure’ – a segment of customers that systematically buy new products that flop. By analysing the data, researchers realised they could predict if certain products would fail if they were being bought by a specific group of early adopters.

Knowing if a product will sink or swim, or a campaign will succeed or flop, is the Holy Grail for most marketers. Now, thanks to the capabilities we now have with ‘big data’, we can get much better insights into consumer behaviour and product trends, and start anticipating rather than reacting.

Companies such as Amazon and Netflix are brilliant at this. They have masses of data to draw on, and have honed their algorithms to offer highly relevant recommendations that drive sales.

You may have already invested in big data technology: you have new and shiny software that captures it, crunches it and presents it to you in an attractive way. You can click your dashboard at any time for a bird’s eye view of exactly what’s going on in your company and precisely what has been sold in the last hour and what your stock levels are down to the last unit.

But then what? What do you actually do with this information? Some things might be obvious, like increasing reorders of a certain product because you can see it’s selling fast.

Others may be less apparent, and you could be missing out on business growth if you’re not able to exploit the advantages of your data.

Let’s take a look at ways that you can really drive your business forward with smart use of data. The key thing is always going back to the customer journey and seeing what you could do better at the various stages.

1. Tracking visitors

Knowing who your actual visitors are can greatly help create more relevant and targeted marketing campaigns in future. Where are customers coming from in terms of region? Did they reach you through paid search or organic search? What content are they consuming on your site?

This can all be used to adapt and refine your messaging and what you feature on your website. The Financial Times (FT) uses its paywall to harvest data on readers: they’re asked to register to read up to eight articles per month for free. Registration requires an address, industry and job area, which enables FT to deliver much more targeted advertising, for example, to a specific industry section.

Editor’s note: A representative from FT has clarified that it changed from the metered approach last year in favour of a paid trial model, by which users can sign up for unlimited access for one month for $1. FT says its analysis shows that in addition to creating a more compelling proposition for readers, paid trials also generate higher conversion rates. 


2. Smoother path to purchase

Once you’ve got visitors on your website, it can be a challenge getting them through the stages of purchase to actually transact. ‘Shopping cart abandonment’ is a major problem – as many as 80% of customers drop out during the process – but data can help you fix this. You can find out where customers are getting stuck: the pain points or bottlenecks where they simply give up and go elsewhere.

3. Optimise customer support

Getting the right level of customer support is critical throughout the customer journey, as different customers have different needs. Using data you can see when people are buying directly or when they need assistance. At Dropbox we have an inbound team who field questions from people coming onto the website. We use this to tweak our content: for example adding more product details or information about security.

Giving customers what they want from the start enables us to reduce the number of people needed for customer support.

4. Run A/B testing

Data gathered through A/B testing – where you randomly assign users to two different groups and measure the effectiveness of each – gives you instant feedback on what’s working and what isn’t. This is vital for us as a marketing department: not only can we track everything, but we can also change it in real-time.

One thing we do as part of the new customer’s journey is an email nurture campaign. We put different copy in the five emails we send them over five weeks, and see what performs well and what has the best click through rate.

Another example is fashion rental company Rent the Runway: their data showed that women were 200% more likely to rent an outfit if they’d viewed a photo of it on a real woman, rather than a model. From there it’s an easy step to adjust the imagery on your website.

5. Automating your marketing

Marketing automation uses all the information you know about a person to understand their needs and wants to deliver the right information. This could be knowing exactly when someone is ready to buy through their behaviours and interactions across your channels.

A prospect may have just visited your pricing page and downloaded an e-book from your website. This can trigger a piece of communications providing a special one-time offer and links to more relevant content they are interested in.

6. Planning advertising

Another area that data can really help with is planning advertising spend. A large company may invest millions of dollars in an ad campaign. With that amount of money at stake, it’s vital that the campaign reaches its target market effectively. Data helps you cut up the budget between different channels: video, paid ads, podcasts and so on, to create a fully integrated campaign.

It’s very important to measure it and track data, and adjust your channels if necessary. Rent the Runway’s data revealed that 25% of its customers were adding an accessory to their designer dress orders, so the company ran an upsell program from this.

The good news is that you no longer have to be a technical wiz or need a degree in computer science to make sense of data. Of course you need data in a presentable form to be able to spot patterns and gain insights, but there’s no need to get your head stuck in spreadsheets. Digital tools such as Tableau and Domo enable easy data visualisation and analysis, letting you connect all your data from different systems into one place that can be viewed on mobile or desktop.

With the right tools and approach, every business can make data-driven decisions, and grow faster and become more competitive as a result.


Deeps De Silva is head of marketing APAC at Dropbox.


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