I’m often asked whether big data can provide the same opportunities for small businesses and independent traders as it can for big corporations. My answer: absolutely! While the average small business has less self-generated data than big players like Google or Facebook, this doesn’t mean big data is off limits. In fact, in many ways, big data is more suited to small businesses because they’re generally more agile and able to act more quickly on data-driven insights. Let’s look at some of the ways small businesses can make use of big data, which I have taken from my book Big Data for Small Business For Dummies.
Understanding what makes your customers tick
Thanks to big data, small businesses can get a fuller picture of their customers – what makes them tick, why they buy, how they prefer to shop, why they switch, what they’ll buy next, and what factors lead them to recommend a company to others. Companies can also better interact and engage with customers by analysing customer feedback in order to improve a product or service. Useful data sources include traditional in-house data (like sales data and customer service logs), social media, browser logs, text analytics, and large, public data sets (such as census data).
Social media has become a particularly valuable source of data, making activities such as identifying niche markets and analysing customer feedback much easier and cheaper. Twitter – where almost all conversations are effectively held in public – is easier to mine than most platforms.
Spotting and monitoring behaviors and patterns allows us to take a stab at predicting where things are heading, how demand for our products or services will change over time, and what will prompt that change. Until recently, trend analysis and prediction often came down to ‘gut instinct’. Now, big data is taking a lot of the guesswork out of that process.
Trending topics flash across Facebook and Twitter every day, making it easier than ever before to work out what people want. Services such as Trendera and Trend Hunter collate trend data and use it to answer specific questions for businesses. In retail, online and offline customer behavior can be measured to microscopic detail – even down to how someone moves around the physical and online store. That data can be compared with external data, such as the time of the year, economic conditions and even the weather, to build up a detailed picture of what people are likely to buy, and when.
Checking out the competition
In the past, understanding your competition was limited to industry gossip or looking around rivals’ websites or shops. Some might go as far as pretending to be customers in order to find out more about a competitor’s service or product. These days though, you hardly need to leave your desk to find out what the competition is up to; financial data is readily available, Google Trends can offer insights on the popularity of a brand or product, and social media analysis can illustrate popularity (i.e. how often a company is mentioned) and show what customers are saying. Again, Twitter is particularly transparent place to start. All the information you gather can be compared with your own brand; for example, does your competitor get more mentions on Twitter? How do their Twitter conversations with customers compare with yours?
Keep in mind that it’s also easy for your competitors to glean more information on your business than ever before. There’s no way around this, but you can stay one step ahead by keeping up-to-date on the latest big data technologies and uses.
Big data is also increasingly used to optimise business processes and everyday operations. With any business process that generates data (for example, machinery on a production line, sensors on delivery vehicles, customer ordering systems), you can use that data to make improvements and generate efficiencies.
For manufacturing or industrial companies, machines, vehicles and tools can be made ‘smart’, which means they can be connected, data-enabled and constantly reporting their status to each other. By analysing this data, organisations can gain real-time visibility into their operations and look for ways to increase efficiency.
Retail companies are able to optimise their stock keeping based on predictions generated from social media data, web search trends and weather forecasts. This allows stores to stock up on the most popular items, ensuring they don’t miss out on sales and reducing the amount of unwanted stock lying around.
Supply chain or delivery route optimisation is another business process that is benefitting heavily from big data analytics. Here, GPS and sensors are used to track goods or delivery vehicles and optimise routes by integrating live traffic data, and so on.
Recruiting and managing talent
Data can help you find the most successful candidates, identify the best recruitment channels and help to better engage existing employees. Most businesses already generate a wealth of HR-related data: absenteeism figures, productivity data, personal development reviews, and staff satisfaction data. As well as this, companies can now access so much more data that wasn’t available before: data from recruitment sites, information from sensors in ID badges, social media data, etc. All this information can be analysed to gain insights that were never available before.
Tweaking your business model
Data can even become a part of your business model, leading to exciting new ways to generate revenue. Facebook, for example, is free to users but has historically generated income from advertising. Now the company is capitalising on the huge amount of data it has on its users, by making certain data available to businesses. Some of this data is available for free but some of it you have to pay for, creating a new income stream for Facebook. There are many opportunities now for small businesses to monetise the data they are generating by providing value added services or selling data to customers or third parties. One of my clients is now using data from inbuilt sensors to dynamically adjust maintenance cycles depending on how much their customer use their product.
Big data analytics in small companies can start by simply using all the big data that we are now surrounded by and that other companies give us access to. Ignoring the big data revolution is a very risky approach for any small business to take. I recommend that every small and medium sized business develops a big data strategy to identify the opportunities and threads it is facing from the global data explosion.