How big is big data? By 2020, there will be an estimated 44 trillion gigabytes of digital information. Small businesses can use big data to determine specific industry and demographic trends. Big data is the pathway for local companies to compete with big enterprises. However, you have to know how to interpret the massive inflow of information and put it to use in a meaningful way. Here are a few tips to help a small business do just that.
Don’t Focus on Every Piece of Data
Big data can be overwhelming to analyse; there is just so much information to dissect. It’s not necessary to examine every single piece of information; some simply have no relevance to your company.
The number of Facebook likes, for example, is a common metric. However, this doesn’t mean it’s applicable in every instance. Yes, it’s a fairly good indicator of your social media presence. However, it may be too general for acquiring specific details. How many of those followers read your content or clicked the link to your site? For a small eCommerce company, more relevant data may include:
- Number of people that clicked on an email newsletter
- Number of site visitors that explored your site beyond the home page
- Number of clicks or enquiries for a particular product
The bottom line? Don’t read too much into every little detail. The number of views and comments on a company Throwback Thursday post on Instagram, for example, is probably not relevant towards your business ROI objectives.
Set Clear Objectives
You can determine which set of data is useful if you set clear goals. If your goal is to increase the number of signups for your loyalty program, for example, then data to analyse may include:
- Click-through rate for links to your loyalty program page
- Age and gender demographic of current members
- Popular sellers among loyalty members
The more specific your goal is, the more use you can make of big data. A goal like increasing ROI is too general. Be more specific. How much do you want to increase it by from the previous year? When do you hope to achieve those figures? You should have some interim goals in between to reach your bigger objective.
Only Use Quality Data
Not all data are created equal. A lot of data may be too broad to be reliable. Click-through rate, for example, may not be high-quality data in of itself. Does that data include the number of actual sale conversions? Of those that did not complete the sales process, how far along the sales funnel process did they get? Quality data needs to be specific in this way. It’s almost never enough to rely on broad percentages. In most instances, data can be broken down further to acquire genuine, quality information.
However, data that is too specific may be counterproductive. For eCommerce companies, do the geography, hobbies, or occupation of your demographic matter? It may or it may not. If the data is sort of all over the place, then it’s information that probably can be skipped over.
Identify what the Data Is Conveying
Look beyond the numbers and ask yourself what the data is telling you. If you’re getting high click-throughs but a disproportionately small number of sales conversions, then you need to determine why that is happening. Perhaps the call-to-action needs some tweaking, or you need to include a limited-time offer of some sorts.
Old data can come in useful here. You can, for instance, measure the sales conversion of similar products before and after adding a promotional offer. If sales are remarkably better in the latter, then that data tells you that your demographic appreciate good deals and freebies.
Big data points the direction for better ventures. Meticulous examination of relevant data helps you identify potentially lucrative opportunities. If figures yield a trend towards a particular product or product category, then that is an indication to invest more heavily in that area while discontinuing underselling goods and services.
Also, keep in mind that data does not just come in numbers. Data may also include written responses from a survey or poll. If numerous customers indicated on a survey that they like product X but are more attracted to product Y’s bargain price, then that is clear-cut data that doesn’t even need interpretation. Multiple opportunity pathways become available right there: lower product X’s price, increase product X’s value, etc.
This is the age of data-driven marketing. The small companies that get ahead are the ones that sift through their data with a fine-toothed comb. Big data reveals a very significant trend about your consumers. It would behove of your business to pay attention.