So much of what we do in commerce these days is automated. If you’re worried about robots taking your jobs, the good news is that the software is mostly just doing the boring part of the job for us. Here is everything is you need to know about transactional data.
For the time being, we still need men and women of vision, people who can spot an opportunity where others cannot, people who can bring innovative new products and services to the market, and add a personal touch that turns a customer into a loyal friend of the business.
Most of the automation in commerce today has to do with getting a lay of the land.
And as long as we’re going with a geographical metaphor, let’s put it like this: Transactional data is to commerce as sending a surveyor out is to mapping a construction site. It’s just the raw data. You can take that data and turn it into a roadmap and then build or pivot your business and marketing plans around it. The transactional data is, as the name implies, created at the point of transaction.
Forms of Transactional Data
Transactional data is created around three key points of reference:
- A number or measure
- An object, and…
These points of reference are tracked throughout the day, following a customer’s purchases. The resulting data will be logistical, focusing on points of data like physical location, financial, looking at invoices and inventory and so on, operational, covering human resources concerns, and digital, looking at things like where a browser is clicking, what they’re downloading, watching, reading and so on.
None of the numbers you learn from this data are of any use on their own. If you find out that someone bought a sixteen-ounce bag of coffee beans, all you know is that they bought a sixteen-ounce bag of coffee beans. You don’t even know if they drink coffee or if they were shopping for someone else. You don’t know if they buy this brand regularly or are just trying it out.
But if you take all of the data together, you can see patterns start to form.
If they buy the same bag of coffee every week, then you can see that they probably drink a lot of coffee. Or at least, for all intents and purposes they do. Even if it’s for someone else, they’re the designated coffee-buyer. This means that they would probably be receptive to ads for sales and saving money on bulk purchases. It means that they would probably be looking for new coffee-making equipment like a French press or a brewing machine now and then. It also means that they’re probably not interested in an instant coffee machine. If they’re buying beans, then they have the time to grind and brew the coffee themselves and they’re not interested in having it ready-made with the push of a button.
Putting the Transactional Data to Use
Transactional data can be put to use in any number of ways, but it’s typically going to come down to one of two things:
- Ad targeting, and…
- Adjusting your business plan on a broader level
In the first example, ad targeting, what you’re going to be doing is looking at one customer’s data and figuring out what advertisements to show them.
Or rather, you won’t be looking at it, but the algorithm will. This is how Facebook knows to show you, say, a sale on gym socks right after you bought a pair of Nike’s. Ask the average internet user and some people might tell you that ad targeting is creepy. But the numbers generally show that it works. Being shown ads might be annoying no matter who you are or what you’re being shown, but it’s less annoying to be shown an ad for something you care about that for something you don’t. You don’t want to sit through all those pharmaceutical ads on daytime TV if you’re not experiencing those symptoms, but if you were really into Indian food and they showed you an ad for a new curry place, you might write the address down.
Personalized ad content is critical in the modern business place. We tend to waste so much money reaching out to people who just don’t care what we’re selling, and with transactional data, we no longer need to. Obviously, algorithm-based advertising isn’t perfect. Now and then you see Facebook ads for things that you have zero interest in. Maybe you let your cousin use your computer to buy a set of car speakers, and now they won’t stop showing you auto and audio gear, even though you could care less about customizing your car.
But ad targeting through transactional data helps to remove a lot of the guesswork. Maybe one in two people who see your ad will actually find it relevant, but with the old method, you were lucky if that number was one in twenty. Personalizing the advertising that we see on the Internet is helpful to both the customer and the business.
On a broader level, you can use transactional data to adjust your business on any number of levels by studying the means and averages and patterns across thousands of customers at both your business and through market reports on your industry at large, and on related or parallel industries such as those that have the same general demographics or those that operate in the same physical territory.
Essentially, transactional data is the foundation and the starting point of big data. It’s good to have a mathematical snapshot of the supply side. It’s nice to know what time of year it will be easiest to grow tomatoes and where you can buy inexpensive land and so on. But without demand, there is no business, just a hobby. Transactional data tells you what you need to know about the demand side of the industry.
By looking at the numbers from thousands, or millions of users (and maybe even more than that), you can discover any number of crucial insights, for example:
- When and where your target demographic is shopping. If they’re usually doing their shopping in the afternoon and they don’t like to travel more than a few miles to pick up their groceries or buy their clothes, then that’s something you should know. Likewise, whether they prefer online or in person shopping.
- How long people spend browsing a site before making a purchase. If they’re usually in and out within two minutes, then you can assume that they know what they want and they’re here to get that and move on. Unless the deal you’re showing them is relevant to what they’re buying right this instant, then they probably don’t care. If they like to click around a bit before adding anything to their shopping cart, then it might be more useful to run special promotions on the site.
- Where people are coming from. This is easy on the internet. Maybe they click through Facebook and Twitter to find your shop. But it’s possible to gather this data from physical locations, as well. If they stop in after hitting up Starbucks, then it might be time to start talking about cross promotion.
These are just examples.
The insights that can be gleaned from transactional data are effectively endless. What we’re doing is looking for patterns base on the who, what, when and where of our target demographic’s spending decisions, and from the answers we get to those questions, we can figure out the why, and once you have the why, then you can go about figuring out how best to serve those customers.
If you read some of the opinion pieces out there on transactional data, it paints a picture that is a bit out of step with the reality of the field. It’s not any kind of digital spying, and it’s very hard to put the data towards any ends that are not helpful.
You’re trying to find out what people want so that you can give it to them, all without having to waste their time with surveys and questionnaires, and without having to waste your time, money and resources on costly trial and error.
Transactional data is collected by the software from transactions between customer and business, and generally speaking, the data does not itself wind up in the hands of a human who is going to look at it and say “Debra bought five bottles of wine last week.” By the time you see the data, you’re not going to know the names and faces of the people it came from.
There is no way to create a foolproof approach to transactional data, at least not just yet but, you can use dashboards like bizlitix to help you have a better understanding of your business and give you great insight, however.