Join the first monthly live stream event of Astrato by Vizlib and learn more about playing the data where it lives! 🎙 Register now

Back to blog

Post Black Friday: A treasure trove of data with interactive dashboards

Post Black Friday: A treasure trove of data with interactive dashboards

So, Black Friday has come and gone, your warehouse is fulfilling orders, and you’re totalling up all of the sales. The question is, what happens next? And we don’t mean the Festive season; what do you do with all of the Black Friday data? Use interactive data dashboards to carve it up and look for the nuggets of gold buried deep within.

Black Friday is the perfect way to shift dead stock and turn around your profits for the year. At least, that’s what it was originally meant to do. Since its inception in 2005, Black Friday has evolved from a single day of consumers waiting in line at midnight after Thanksgiving to get the best deals, to online shoppers wading through a slew of deals for the whole of November. The iconic name no longer consists of just a single day and customers expect more from stores.

Besides having stellar deals for customers, the sales day – sorry, month – is a wealth of data for any retailer, chain, or supplier. There’s so much information contained in those transactions. Let’s break it down.

Drill down into what actually sells and when

The obvious answers here are big-ticket items. Black Friday has been synonymous with TVs, video game consoles, home appliances and other electronics. However, you’ll want to drill down further and see which other items customers wait for and purchase during the big sale, or which items only move during Black Friday.

Let’s look at the average mass-market bookstore as an example. Certain prose authors, like Terry Pratchett or Sarah J. Maas or the collected works of Edgar Allen Poe will always sell. It doesn’t matter if they’re sitting on a shelf at RRP or discounted by 30%, those books are bound to move. But what about non-fiction titles, such as self-help books or “easy-to-understand guides” to investing? Do they only move during Black Friday at a heavy discount? Is it even worth keeping stock of these items for the other 11 months of the year or will they just take up valuable warehouse space? These questions should be applied to every single item that you sell to the public.

By using an associative engine, like Qlik Sense, it’s easy to dig into your sales data to find information gems. In drilling down into this data, you could save your company money by eliminating stock that doesn’t move at any other time of the year or using your sales power to leverage better discounts with suppliers and manufacturers.

Understanding payment methods to plan ahead

Another large part of Black Friday is the transactions themselves. The general idea is that credit cards dominate online purchases, but does Black Friday bring new customers to your store who utilise alternative payment methods?

By understanding payment methods, it’s easier to plan accordingly for credit and debit cards, electronic cash transfers, PayPal, or even cryptocurrency. This gives stores the ability to negotiate better transaction rates for the month of November – after all, every 0.5% counts.

With the power of Qlik Sense and Vizlib, it’s easy for anyone in the organisation to decipher sales data and plan ahead. Workers in the buying department might want to exclude certain high percentage payment methods from being used with a product category, or marketing might want to incentivise customers to use a different option.

Making the right purchases with interactive dashboards

“But what if everyone in the company needs to access the Black Friday sales data?”

That’s where Vizlib’s range of feature-rich products for Qlik Sense comes in. With Vizlib’s easy-to-use, no-code functionality, any individual in the organisation can create custom and interactive dashboards. With 25 chart types in Vizlib Library alone, users can display data the way they want.

Adding Vizlib Self-Service to the mix gives employees the power to create web-like familiar interfaces that are simple to use and encourage broader data usage.

Sign up for a demo today!