Improving Your Business with Data Processing

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Data processing is an elusive and complicated experience for many businesses. What it is and how it can be used remains primarily misunderstood and, perhaps for that reason, dramatically underutilized.

While big business has finally come around to embracing data implementation—leading to a significant rise in data-driven jobs—public perception continues to frame data processing and implementation as a leg up and not the business requirements that it is quickly becoming.

This article looks at some of the many ways you can use data processing to touch every aspect of your business.

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What is Data Processing?

improving your business with data processing

As the name might suggest, data processing is the art of turning large swaths of untamed information into descriptive, actionable insights that your business can use to maximize profit and improve processes.

Several steps go into data processing.

Collect Information

The process starts with computers pulling information from all of the sources they have available to them. This may include data warehouses or other sources where companies can store the information that belongs to them.

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Data Storage

Now that the information has been compiled, it must be stored to comply with government regulations. This means implementing security features and procedures to keep customer and company information safe.

Particular legislation has been drafted worldwide dictating how to store data, so make sure you get it right. Failures come with stiff penalties, but they can also cost you consumer confidence if you aren’t careful.

Prep It

During the preparation phase, data is checked for redundancies and cultivated to ensure a high-quality well of information. You will eventually be able to derive valuable business insights.

Process

Now that the data is clean, it can be processed through databases and algorithms to produce conclusions.

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Analyze

Now that the information has been processed, it’s time to analyze it and distill it into a presentation-worthy form.

These steps conclude with information set that you can use to help businesses find success with various operations. Below, we look closely at how you can use data to improve business functions.

Marketing

Marketing has always been a numbers game, so it should be no surprise that data processing has a significant role in how your marketing department should be operating.

You can use processed internal data to get a good idea, not just of your average customer but also of your best customer. Most businesses have a small percentage of customers who are likely to stick around for the long haul and go in for upsells and big spending. In marketing, these people are referred to as the “ideal customer” (not very creative, perhaps, but suitably descriptive).

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The ideal customer can be identified through data using existing customer metrics to create an ideal customer profile or ICP. With an ICP, your marketing division can craft campaigns tailored to people most likely to be big spenders when they discover your business.

Marketing can also use third-party data sources, such as a social media analytic application, to further refine their campaign. For example, turning your social media ad metrics by your ICP may inform what time of day you release ads or even what platforms you put the most money into.

This is good for you because it means spending less money on more effective ad campaigns. It’s suitable for the customers as well. Rather than being bombarded with useless ads, they are directed toward a product they will likely use and enjoy. Win-win.

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Upsells

You can also use internal data processing to identify opportunities for upsells and cross-sells. This can be a significant boon—many businesses make the vast majority of their “new” sales to current customers, putting a hefty premium on being able to identify people who are going in for more.

Using sales and billing data, you can funnel customer information directly to your sales department through the CRM, allowing them access to clean, accessible reports on customers who might be interested in buying more.

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You can also use your ICP to survey existing customers to find out if there is anyone who would likely enjoy more goods or services than they are currently getting.

Furthermore, you can use data processing to identify what upsell packages are the most popular, which produce the most perceived value, and which can probably be ignored by your sales department. Less effort is wasted. More revenue is generated. More customers are protected with products or services that they want.

Personnel Restructuring

You can use data processing to get insights into the efficiency of your internal operations as well. Using performance data and productivity analysis, you may learn, as an example, that one department has four people doing work that could comfortably be handled by three.

This information could, unfortunately, lead to downsizing. Or, it could also lead to cross-training or personnel restricting that allows your employees to make more meaningful use of their time while also boosting overall productivity within your company.

Alternatively, data may also indicate that you need more personnel to fulfill emerging needs or help your existing staff with increasing workloads. Manually structuring your staff can involve a lot of guesswork and hunches. Data adds objectivity to the process that you can’t get through other means.

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Customer Service

Data processing can help improve customer service by examining customer communications and activity patterns. Happy or dissatisfied customers will never reach out to tell you about their experiences.

This can be an obstacle for a business that wishes to improve its customer service. Data processing and implementation can help by distilling the information you have into structured, comprehensive reports that can be used to change policies or even lean in harder to practices that people do like.

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Customer Attrition

Customer attrition—or churn as it is sometimes called describes the phenomenon of customers leaving your business for other pastures. It’s a natural process that you can’t avoid.

On average, about five percent of most businesses’ customers will fall off throughout a year. As long as they are replaced at a great enough rate to allow growth, you can still have a healthy business.

Still, high or not, your attrition rate will always sting. This is particularly true for businesses that depend primarily on recurring or repeat customers. Data dan help you keep your customers coming back.

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For businesses operating regularly (think SaaS or other subscription-oriented business models), you can use billing data to determine what phase people tend to leave in the customer life cycle. For example, data might show that most of your churn happens at the three-month mark.

Knowing this, you can then direct your sales or customer success team to work hard with customers up until that point to make sure they are finding success with your product.

You can apply similar methods to abandoned checkout carts at an e-commerce store or even brick and mortar businesses. Data is essential for this consideration because most disgruntled customers never articulate their displeasure, leaving you with little recourse for improvement.

On the other hand, data allows you to identify gaps in your service and fill them quickly to keep customers coming back for more.

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Supply Chain Management

Much has been made of supply chain management since Covid-19 struck. From grocery stores to tech-related businesses, the world over seemed to press pause for the better of two years. Because of social distancing?

The global marketplace has made it so that items from all over the planet can go into a single product. This system works well during times of peace, allowing socio-economic development and competitive pricing. Unfortunately, as Covid has shown, the system can be surprisingly fragile.

Data, coupled with algorithms, can help automate and improve many supply chain management-related tasks. Select routes that are most conducive to quick turnaround times. Avoid product channels that are likely to be disrupted by war or disaster. Pivot into local solutions that are quick and easy.

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This is good for businesses, which could lose weeks or even months of productivity to a supply line disruption. Still, it is also vital for the communities that depend on products like car parts or healthcare equipment to arrive as scheduled.

Obstacles

Some obstacles can stand in the way of sound data processing and implementation. For example:

Low-Quality Data

Many things can diminish the quality of data—human error, system failure, or simply outdatedness. Information ages like milk: not so well. If it isn’t updated and tailored regularly, it can quickly steer you in the wrong direction.

Maintaining high data quality has been a severe concern in the business world over the last several years. It’s also necessary for exemplary data implementation.

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No Strategy

Since the digital age, businesses have been accumulating massive swaths of information that they never really knew what to do with. Data processing makes the information more understandable, but it still won’t get you very far if you don’t have a strategy for using it.

Talent Shortage

Data processing and implementation hinge on having the right people. Data analysts and scientists are in high demand and short supply. So are data marketers and other similar professionals. Without well-supported, qualified specialists, a data implementation project has no chance.

No Support

Data implementation is sometimes seen as an initiative that sounds good on paper. Businesses may buy into the tech and personnel to look like a forward-thinking companies.

Indeed, the person who began the initiative may have done so with the best intentions. However, if data processing and implementation are not being embraced from the top down, it will never take off.

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Data Siloes

Data siloes occur when you cannot share information fluidly across the different branches of your business. For example, if your sales team cannot access information from the billing department, they will have difficulty using their data to identify upsells.

Data siloes are typically the result of having a poorly coordinated tech stack. All departments have various tools, but if they can’t integrate and communicate, they are holding you back, both in terms of data implementation and, most likely, in many other ways.

Developing a Single Source of Truth allows businesses to have a single set of information that everyone can access. Data has entered automatically through integrations, eliminating the possibility of error. The result is clean information that can be used by anyone who needs it.

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The problems above can be difficult hurdles to clear. However, it all begins with a commitment. When management prioritizes data implementation and makes suitable hires, many other concerns will naturally occur.

It does take an upfront investment. However, data-capable companies more than recuperate the expense with operational efficiency.

A Business Requite

New technology begins as a business edge and quickly transitions into a requisite for staying competitive. Data processing and implementation now fall quickly in the latter category.

It touches every aspect of your business, making you agile, flexible, and efficient.
To get in while the going is good, consider staffing data professionals who can cultivate and shape your information caches into insights that will allow your business to survive and thrive. If you don’t, the competition certainly will.