For many companies, competitive pricing analysis is the key to increasing revenue and staying ahead of the competition. Retailers that can collect and analyze pricing data, map their position against competitors, and offer optimal prices are the companies that catch the attention of buyers first and foremost.
But how can you collect pricing data in an efficient manner? Not all stores have a webshop and even when they do, prices can vary significantly across stores, especially when they are geographically wide apart from each other.
That’s why companies invest a lot of money in sales representatives who visit stores and manually write down the prices. As you can imagine, this is quite a time-consuming and error-prone task that has to be performed at least once per month.
Wouldn’t it be easier to simply scan the shelves with the help of an OCR SDK on your smartphone and automatically capture the price tag data within seconds? In this article, we will explain how this exactly works and what you need to get started.
What is Optical Character Recognition (OCR)?
Let’s start by explaining the basics. If you are already familiar with OCR, you can skip this part, but it’s good to start on the same page. So what do we mean with OCR?
OCR is a widely used technology for recognizing text on documents, such as scanned documents or photos. It is used to convert virtually any type of image containing written text (i.e. typed, handwritten, or printed) into machine-readable text data. From here, processing the data in your database and using it for further analyses is super easy.
Many companies consider OCR as an essential technology for automating their workflows. It helps people work faster with minimal errors in data capturing, data entry, document verification, and many other tasks.
Now, let’s have a look at how OCR can help you to automatically read prices from price tags.
How does OCR work on price tags?
In order to capture data from price tags, the first thing you need is a scanner, smartphone, or another hardware device with OCR capabilities. Usually, a smartphone is used in combination with an OCR SDK.
An SDK, short for Software Development Kit, is a set of software tools and programs used by developers to create applications for specific platforms. It includes a range of things, including libraries, documentation, code samples, processes, and guides that developers can use and integrate into their own apps.
The advantage here is that developers don’t have to build all the components of an app themselves, but they can “use” the work of others, saving them loads of developing time and money.
In this way, it’s relatively easy to integrate an OCR SDK into your own application, enriching it with the OCR capabilities you need to detect objects, such as price tags, and extract data from them.
We can imagine this sounds a bit technical, so let’s describe the steps in the OCR process one by one.
The main steps of the OCR process
The basic process of OCR for price tags consists of several steps, starting with importing images, recordings or (PDF) files and ending with exporting the recognition results:
- Price tag import
- Image pre-processing
- Image to text conversion
- Structured output
Price tag import
The first step is providing a recording, picture, or PDF file of a price tag to the OCR software. When the SDK identifies a price tag on a shelf, it draws a bounding box around it and confirms that it detected a price tag.
To increase the recognition accuracy, the quality of the recording or image should be optimized during the pre-processing step. The SDK applies a wide range of functions such as image rotation, binarization, and de-skewing to enhance the image quality.
Image to text conversion
When the image/video quality is high enough, the OCR SDK will start extracting the data from the price tag. The image is analyzed for light and dark areas, where the dark areas are identified as characters that need to be recognized, and the light areas are identified as background.
The dark areas are then further processed to find alphabetic letters or numeric digits. When all text is identified, natural language processing (NLP) helps to determine which text has what meaning. In this way, the SDK is able to determine what text belongs to the description, what numbers belong to the prices, etc.
Just having a plain text file is not as useful if you want to use the data for pricing analyses. That’s why the SDK takes the text and converts it into a structured output. Typically, this is done in a JSON format, which is commonly used for transmitting data in web applications.
From here the price tag can easily be processed into your database or other software.
What data can you extract from price tags?
Now that we have covered the OCR process, you might be curious to know what data can be extracted from price tags. This depends a lot on what is depicted on the price tag of course, but in most cases, it comes down to the following data points:
- Store name
- Product description
- Product category
- Volume price (price per kg / liter / etc.)
- Product price
- Serial number and/or barcode
- Discount percentage and price
What are the benefits of using OCR?
The main advantages of OCR technology are saved time, saved money, decreased errors, and minimized manual effort. It also enables actions that are not capable of physical copies such as incorporating into a database or ERP system, highlighting keywords, and attaching to an email.
Besides that, collecting data from price tags have two clear advantages for retail stores:
- Enabling a deeper understanding of the market
- Improving marketing and sales strategies
Enabling a deeper understanding of the market
Collecting data from price tags helps you better understand consumer behavior, and identify how you position yourself against competitors.
The more information you get from customers and products, the more you can adjust your business to their needs. It will become much easier to understand what customers are looking for and what they are willing to pay for it.
Improving marketing and sales strategies
Having a good understanding of your competitors’ products and prices can help you develop marketing and sales strategies. This is especially the case when your products are sold in the same location.
If you see, for example, that a similar product of one of your competitors is priced lower than yours and sales suffer from it, you can choose to run a special promotion or discount campaign for that product.
As such, collecting price tag data can help companies in an extraordinary way. With current technical developments, there are no more excuses. Start automating and digitizing processes and gain that competitive advantage!
Yeelen Knegtering, CEO & Co-founder of Klippa, is passionate about developing digital products that help people to save time on administrative hassle and spend time on the things they love. With a degree in Information Technology at the University of Groningen, he started Klippa with the idea that there had to be a better way to organize and manage receipts. Now, Klippa is a document digitization company with a focus on digitizing and automating document streams for companies.