Scalr.ai

Building Data Capture Services To Collect High ROI Business Data With Machine Learning and AI

Matt Payne
·
January 27, 2021



If you’ve ever bought something from Amazon, Etsy, eBay, or another huge online retailer, you’ve already experienced how ai and machine learning can transform buying online. What you can’t see is how these businesses use these same tools to create backend data capture services that gather high ROI data for them that pushes their business forward.

Data capture services from object recognition models

It doesn’t take Facebook, Twitter, or LinkedIn long to figure out what you’re interested in based on your location, occupation, or what you search for online, either. New smartphone? Local yoga classes? Restaurants in your area? You’ll start seeing paid and pop-up ads before too long after you’ve done a search for something. 


AI gives e-commerce companies the ability to quickly and easily make new recommendations based on things like hotjar heatmaps, what keywords you liked, or what facebook pages you like. Or how a SaaS platform can increase conversions by using a deep learning model to optimize it’s funnel, and while it's important to businesses to use these tools in the real time moment, an added benefit of machine learning or AI models is the long term data collection services they include. 



What you don't see as a front end customer or user is the benefit of how these ai tools are used to capture more data to improve the company's future performance. What the most explosive growing companies are realizing is deep data collected from machine learning and ai tools is incredibly useful and powerful. The insights these tools can see and collect are difficult to gather through conventional methods, which gives these companies a serious edge on the competition. 


As top of the line companies continue to move towards being data driven and automated business processes, the extra data collected from use of these tools can be as beneficial as the actual tool itself, especially given the data captured can normally be plugged back into the model to optimize and increase performance. 



Why Is Data Collection So Important? 

Data collection to store new data

Today’s companies need to know more than just the bottom line. Marketing is more than just a catchy slogan. Companies need to know who’s buying their products or services, why, where, and what they want--or don’t want. Data collection services for information on customers, users, and in some cases, employees can be vital to a company’s survival. 


Collecting company data is capturing previous events in order to find recurring patterns. With data, the next step is to build predictive models with machine learning algorithms that use those trends to forecast future activity. 


These models are only as good as the data used to build them, so it’s important to start with the correct and relevant data. 


But there is more to it than just collecting company data. Effective use of data goes a long way in making business decisions like marketing, performance, and problem-solving. Collecting and analysis of your company’s data can also help you understand your customers better, as well as improve efficiency and processes. 


Small and medium-sized businesses can use even their basic data from their social media and websites to learn about: 


  • Customer acquisition and retention
  • Customer service improvement
  • Increased efficiency in business operations
  • Finding and correcting the marketing campaign failures
  • Understanding your company’s performance
  • Observing social media activity and interactions
  • Sales trends predictions


It’s also important to focus on high-quality data, rather than just gathering data for the sake of it. For instance, high-quality data can indicate the marketing campaigns your customers respond to best, allowing your company to tailor those campaigns accordingly. It’s important to understand the data, and not become lost in it. The right tools can help you understand your company’s data so you can use it to your advantage. 


The right data can also better define your buyer’s persona, their favorite products, and a better idea of their trip through your sales funnel. You’ll be able to fine-tune their journey and give them more incentive to convert. 

Automated Data Capture Services




Automated data capture (ADC) is the collection of data that helps speed up the organization and use of the information your company needs. Adding automated data capture tools eliminates the rote work of manual entry frees up employees to focus on customer service and reduces labor costs. Most of the time you can take systems that are already using data and collect higher ROI data as a result of your models.

barcode and label data using OCR

There are several models that are perfect to collect data automatically as they work, including: 


  • Deep Learning Models
  • Optical character recognition (OCR), used for typewritten documents, such as letters, bank statements, legal documents, and the like
  • Optical mark recognition (OMR), used for documents with “check boxes,” such as academic tests with multiple choice options, surveys, polls, etc. 
  • Intelligent character recognition (ICR), used for handwritten documents. This has an accuracy rate of about 50% to 70%, but can improve by continually training the algorithm
  • Intelligent document recognition (IDR), a further refined capture that can recognize patterns, formats, and extract data both from text and tables, from physical paper as well as digitized documents. IDR can also sort documents according to category, then extract data as needed. This function can significantly reduce the time needed to find the most valuable data needed for financial forecasting. 
  • Voice Recognition and Natural Language Processing (NLP). Most often associated with smartphones and smart devices, NLP can be added to data capture systems for multiple functions. Teaching AI to recognize human speech and react accordingly as well as processing data. 
  • QR (“quick response”) Codes are everywhere, from the back of packages to magazines and even posted in stores. These little codes can hold much more information than a barcode, and are easy to scan with a smartphone. QRs can direct a customer to a website, social media pages, offer a discount, or give a customer a range of information  quickly and easily while collecting important metrics. 

Any one of these methods can gather great image or integer data for your company. Combining two or more can help you build a bigger database for future models or analytics. 

Different Types Of Data Worth Gathering


Of course, personal and transactional data are essential parts of a company’s customer list. At first, a name and email address are all that’s necessary until someone converts and makes a purchase. At that point, you’ll need a mailing address. 


Keeping transactional data is also important. It’s not only important to know what a customer bought, but when. Are they only shopping with you around the holidays? How often do they buy from you? This kind of information can help you tailor offers to each customer the way Amazon does, but not intrusively. 


Other data, such as demographics, can be obtained later, and over time. Information such as: 


  • Age
  • Gender 
  • Profession
  • Location
  • Household Income 
  • Education
  • Past buying decisions
  • How they found your company, or why they left
  • Why they buy from you (Speed? Efficiency? Price? Brand recognition?)
  • How did the customer find out about you--referral, Google search?  
  • How likely is a customer to recommend your company/product/service to others? 
  • Other relevant data, such as:
  • Contacts and contact information
  • User experience data (such as in-app ratings)
  • Purchasing behavior (when was the last time they bought something?)
  • Social media interactions
  • The last time they accessed the app or signed in


On the flip side, it’s important not to ask for too much customer data at once, or overwhelm them with emails or other contacts. 


These data points can help you build your basic profile for each customer as well as develop your customer persona. With a good CRM, all your customer data can be kept in one place and ready for whomever needs it, and get in touch with them whenever you like. 

Machine Learning Tools That Can Collect Data For You

It’s always interesting to think about new ways to use ML to increase efficiency and create better outcomes in business. Turning over repetitive rote work to an ai system means more human capital dedicated to the hands-on work that machines can’t do. 

So what models can you employ that collect data in place of humans, and make the data easier to use? Some of the most popular tools businesses use include: 



  • Buyer Intent Models: It’s a software that gives your company information on a customer’s purchasing journey using  predictive analysis, mapping, and your competitor’s data. E-commerce companies can find out exactly what customers will or won’t buy, and when. The software learns the patterns of previous buyers and users and begins to formulate different groups of customers. These buyer intent models can take any many different fields of past data to analyze what a potential buyer might decide to buy.



  • Facial Recognition Models: This is one of the best examples of data collection, and especially helpful for retailers. Face detection is the most prominent of a person’s biometric identifiers, and helps retailers to KYC (“know your customer”) on a deeper level. Not only can an individual be identified when they walk in, facial recognition can recognize what interests each customer, and even when the customer is unhappy.  This software can analyze a shopper’s behavior to discover their likes and dislikes, and improve both purchasing and checkout. The system can provide floor staff with customer information gleaned from social media and other profiles and offer a more customized experience. 


  • AI Finance Technology Forecasting Models: forecasting is a labor-heavy, hands-on process using considerable manpower to review data, run numerous calculations, and come up with potential outcomes for a company’s various markets. AI can process this data at higher speed, as it improves accuracy. This is not to say that financial people are dispensable; rather, the AI gives people better information to work with. Using more efficiently processed information, a company can make better forecasting decisions for their financial future.  




Industries Using AI-Collected Data 

Nearly every industry can benefit from using AI, machine learning, and data collection services. 


Retail is the obvious choice since it’s one of the fastest industries to respond to trends. Chatbots can begin the conversation and quickly increase the amount of data gathered from each customer. Capturing data such as buyer intent 


AI also helps manufacturing respond to trends as well as improve efficiency in operations. Involving your data capture services in things like inventory management forecasting, 


Transcription companies are increasingly utilizing AI and machine learning to transcribe audio files better and faster than before. Automated transcription software can give as much as 95% accuracy, making editing faster and easier. 


In the age of COVID, AI can quickly process data to help healthcare practitioners decide on the best care for each individual patient based on their medical history, symptoms, and other factors, which allows you to build a data capture service that works in real time. 


AI is also transforming medical transcription. Last year, Amazon introduced its Medical Transcription Services to give doctors an easier and paper-free way to add notes and consultations to a patient’s records. 


Many doctors still spend as much as six hours a day handling administrative work such as entering information into electronic health records. Amazon’s service allows physicians to dictate their notes and reports directly into the health record system without any human intervention. Using a service like Amazon’s can give physicians and other healthcare practitioners more time for taking care of patients. 


Data capturing can also help banks and other financial institutions detect fraudulent transactions before they drain a customer’s bank accounts. It’s particularly helpful for detecting elder financial abuse both by the financial institutions and for an elder’s family member. Unusual checks or withdrawals, new co-signers added to accounts, and other activity that can indicate fraud or abuse can be detected much faster, and alert the bank and/or relatives immediately. 





Looking To Collect Data Your Competition Envies? 

Scalr.ai is a machine learning consulting company that builds machine learning and AI software tools in house to accelerate your company’s efficiency and positively impact your bottom line. 


Our company specializes in natural language and computer vision systems that give businesses a better understanding of their revenue streams and building tools to make them more profitable. Using our data collection services, we can help you capture important data and put it to good use no matter what industry your company is in. 

Want to talk to an expert?


If you’d like to find out more about what our data capture services can do for your business, contact us today. We’ll be happy to discuss how to incorporate AI and machine learning into your business to increase efficiency and profitability. Want to see other data capture solutions?