While you may think only large enterprises struggle with big data, in fact it’s a relative term – big data is any data set that a business can’t easily store, integrate or analyse. Expert Jeff Healy says that small and medium businesses can benefit from what large businesses have learned about harnessing big data for better engagement and more sales conversions.
1. There’s been a lot of talk about “big data”. What is it?
Big data is the myriad information that is collected and analysed. You might have big data related to how a disease is spread or from multiple sources related to a political campaign, or a business might have big data because it has purchase histories and other data about its customers.
2. We typically think of big data as affecting large enterprises. How can it benefit smaller businesses?
SMBs can benefit from the principles of big data and you don’t have to have access to fancy software. Enterprises and governments combine data sets from multiple sources to get fresh insights, and SMBs can do the same, looking at their customers, products, pricing strategy and so on.
For example, Monkey Logic recently worked with a winery, refreshing their loyalty program. After analysing the data, we targeted 10,000 people with a new e-newsletter, achieving a 40 per cent open rate, a spike in traffic to the site and $100,000 in revenue. We also could see that of the 300 people who got to the shopping cart, only 40 completed a transaction, so we knew there was an opportunity to improve the experience. We could then target the people who hadn’t completed a transaction. All we used was the website analytics and Excel – it was simple, manual analysis of real data.
3. What challenges does big data pose?
Apart from data hygiene, creating actionable insights from big data is
a challenge. Then, if it works, you have to have a process in place to repeat that success.
Another of the challenges of big data is privacy. Businesses can get some very good information from ADMA about the requirements. You should take the moral high ground – be explicit about why you are collecting data and how you will be using it.
The final challenge for SMBs is time – whether you have the in-house expertise to collect and analyse big data, or you’re able to hire expertise.
4. How can smaller businesses use or modify enterprises’ big-data tools or methods for their own big data?
Large enterprises may use Oracle or IBM tools, and SMBs shouldn’t dismiss these larger-end tools – they may offer an SMB product or software as a service. Excel can be a very sophisticated tool, so you might want to take an advanced course. Google, AdWords, YouTube and social media analytics are quite powerful if you know how to use and interpret them. Intuit [in the US] has extended accounting software to an analytical tool. You can use Proficy CSense to combine data sources. The reporter tool, Prism, may be suitable for businesses at the advanced end of the SMB sector. You buy a licence or pay a monthly fee. Start simple and work your way up.
5. What is the biggest mistake businesses make when dealing with big data?
Some businesses lack a clear objective. They might collect too much data without considering why they are collecting it, or they get excited about the new technology and capabilities and jump straight in, but the software alone can’t deliver benefits.
Another mistake is not ensuring that the data is robust and clean. If you put garbage in, you’ll get garbage out.
6. Can you give some examples of businesses that use data well?
A few years back, an Australian retail chain operating in the bulk pet and garden supplies arena was looking to expand its retail footprint. It wanted to make an informed decision about where new stores should be located. With the assistance of an external specialist, the retailer built a planning tool that integrated internal transactional data from existing retail stores with external data from organisations such as the ABS. Information at a suburb level was used that provided details of the socio-economic status of area residents, geo-demographics and the average household expenditure on pets and garden supplies in that suburb.
The combination of these various data sets provided the retailer with a very sophisticated retail planning tool that allowed them to open new stores in strategic locations, with accurate projections on how quickly the new store would become profitable. The model has proven invaluable, as the business is able to test its robustness with each store that opens. The retailer updates the data sets based on a real-time data feed from all its retail outlets, including the newly opened stores.
In the US, media streaming company Netflix used big data from tens of millions of customers to determine what type of content would be successful. They discovered that a political thriller had a high chance of success and funded House of Cards, which received nine Primetime Emmy Award nominations and won a Primetime Emmy Award for original online-only television.
Starbucks has also been operating in this space before the term “big data” was even coined. It integrated online and customer feedback and customer development panels to uncover which parts of the US prefer, say, certain flavours of muffin. Traditionally, you take a sample of 1,000; now, Starbucks can take in the real-time feedback of every customer.
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WA-based agency Monkey Logic helps businesses optimise their database use and CRM programs.
The views expressed in this article are those of the author and the interviewees, and not of Australia Post.
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