Optimize High ROI Business Data with Machine Learning and AI

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?

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.

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.

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.

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.