Business intelligence tools: 2019 tech for analyzing your sales data
February 13, 2019
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Did whoever invented the spreadsheet feel joy?
Yes! And most likely because what they were doing was innovative and necessary at the time for the technology that they helped develop.
The point is that this industry is constantly developing, and forty years later, nothing has stopped. Spreadsheets are still necessary, but when it comes to convenience for retailers, we can’t just settle, can we?
Luckily, 2019 can offer some additional encouragement to make data analysis not sound as painful or bland as the phrase “data analysis.” The 9th International Conference on Data Analysis and Cloud Computing 2019 may be on the way, but you don’t need to travel to the UK for some tips. But if you do, take lots of pictures.
You need data to understand your customers’ shopping habits. How can you turn numbers into action?
The importance of sales data analysis is clear; you can use your sales data to understand the trends, demand, and required preparation. You need data to understand your customers’ shopping habits. How can you turn numbers into action? It’s one thing to collect a bunch of data, compile it, and stare at it, nodding, eyes glazed over. But having all that information is useless unless you have the proper methods to analyze and understand it.
The difficulty with organizing and correlating sets of information is enough to make any amateur’s head spin. Since you likely have enough on your plate, why not consider some ways to better organize that sales data you’ve been attempting to understand?
Artificial Intelligence technology is helping retailers organize and understand their sales data more efficiently.
It’s more than just convenience. AI can give business owners a clearer depiction of the sales data they analyze, specifically with the use of automation, visualization, and graphic organization. And when something has that much -ation, it’s got to be good.
Visual analytics are helpful to retailers as they display the data in an organized and readable format. With helpful qualities like this, AI is expected to open doors for self service with the help of Machine Learning which will make data analytics more accessible and comprehensible for business owners.
At the same time, projections have been made for an increase in Chief Data Officer roles by the end of 2019 for most big enterprises.
Is that an oxymoron? Well, the difference is the size of the operation. Small, experienced business owners will be able to self serve for the most part using AI. But larger operations will most likely not want to risk neglecting their data. In a way, AI is leveling the playing field for large and small businesses.
Does this self service threaten jobs in marketing? SMBs were most likely already doing their best on their own. When technology is augmented, business owners and CDOs alike are able to save some brain power while attempting to understand sales data.
AI is taking the place of time consuming and seemingly impossible tasks, much like a calculator. But this calculator still requires experts (human ones) to make sense of the data in order to make predictions, and further developments. In short, it needs to turn that information into action.
As the world becomes more and more digitized, it’s important to acknowledge that those digital platforms and resources need to be adopted and practiced. The digital world will continue to develop and resistance…Well, resistance is futile.
Make an informed decision
There are many platforms for organizing data, so it’s important to understand the metrics and qualities you need to focus on.
There are many software options that all have similar features and comparable prices. But all of that technology is useless unless you have the right strategy. Without the right data and the right strategy, you’re likely to waste time, money, and customer connections.
Having a focus in place can help you decide which platform to use. In terms of qualities, are you interested in transparency? Accuracy? Organization? All and more?
Without the right data and the right strategy, you’re likely to waste time, money, and customer connections.
Additionally, some key performance indicators for retailers include cost of goods sold, average purchase value, number of customers, retail-conversion rate, number of items purchased per visit, stock turn, and sales per square foot.
“Up in the air” sales data analytics
It’s good to research the different kinds of software to find your fit. But platforms also vary. 2019 is seeing a strong focus on cloud computing.
Clouds have redefined data analysis. They’ve revolutionized the way retailers connect, allowing for accessibility and visibility. Clouds are scalable and make data shareable. And startups and small businesses can avoid spending so much money on their servers.
The information is all there, accessible from any device at anytime. Cloud computing is the solution for big data.
With all this pressure on cloud computing, “eventually, that demand is likely to overwhelm the network, cloud and apps that perform all of those data acrobatics. Edge and fog computing are emerging as solutions that put that processing right at the edge where results are needed.”
Retailers can take advantage of the cloud to better customer service. Understanding customer demands is one thing, but how does that separate brick-and-mortar from ecommerce? Why not do everything online?
Because service is important. In-person shopping still dominates, so in-store expertise and customer care must keep up. Cloud computing can be used to communicate between your online support staff and your in-store staff, understanding a customer’s needs and wants, collecting specific details, and allowing your team to satisfy the customer, and even upsell relevant products.
Knowledge is power.
With all this freedom and easy access comes skepticism about security.
Have you ever been forced to provide your phone number on a form, only to receive a series of phone call offers in various languages? How can you trust that information on a cloud is protected?
What you should consider is the gain and loss of betraying their customers’ trust. Cloud-based platforms rely on their reputation to provide safe and secure networks
When you collect information and store it in a cloud, bear in mind that the cloud is a company. It’s making money off of your use. What you should consider is the gain and loss of betraying their customers’ trust. Cloud-based platforms rely on their reputation to provide safe and secure networks. If you feel vulnerable, take a look at the company’s fine print before you start mining any data.
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