5 Data Management Tips for Small Business
Digitalization has entered businesses, small and big, so rapidly that part of them has still not recognized the power of this essential asset. Regardless of the business size, each year, they tend to double the amount of data they already have at the disposal. Not a tiniest step of a business process goes without constant data generating. But what’s the point of collecting information if your business can’t benefit from it? Thus, data management strategy is among the prime things you are to work out to make profits flow.
Data management for small businesses is considered challenging to handle, especially if you step into it for the first time and find tons of unsorted data generated over months. That’s why if you feel that your business is lagging behind with the data waiting for optimization, the following tips will come in handy.
Data Management & Small Businesses
Running a business, people don’t usually rely on some unclear imaginations about how it goes. They count on accurate real-time figures, statistics, and reports made on their basis. All the data generated during the business processes automation is vital for enhancing an enterprise’s overall productivity. Having easy access to full-scale data about every customer, employee, or transaction made is essential for a company’s intensive growth. Clearly laid out data ready to be analyzed and shared is a must for any competitive and proactive business.
But why should smaller businesses be more aware of their data management strategy? Here are the top reasons.
Higher Cybersecurity Threats
Data management is not only about storing information but about its safe preservation. Smaller businesses tend to have weaker data management as their data seem of less strategic importance than that of large corporations’. Thus unprepared for such attacks, they become an easy mark for cybercriminals and are less likely to recover quickly from data leakage.
As the budget of small companies is generally more limited, being cost-effective is crucial, especially in the beginning. Prudent data management is the key to reducing unnecessary spendings on accidental work duplication or goods oversupply.
Smaller businesses are highly responsive to market change as it’s easier for them to switch the niche or expand it according to the customers’ demand. Having data in front of the eyes helps to make adjustments quicker than other small companies with weaker data management status.
Important data preservation
Since small companies are less aware of data management, they not only miss out on the vital information but also don’t back it up in case a cyberattack or another complication appears. The loss of original company data may cost it the place in the market.
Precise decision-making process
Running a business can’t be deprived of risks and setbacks, but while more prominent companies may have enough strength to recover, the smaller ones have fewer chances to revive after a single wrong step. That’s why data optimization is essential for daily analysis, safe business planning, and statistics-based decision-making processes.
Essential Marketing Data
Clearly, small businesses are more vulnerable if they are not aware of the importance of data management. But running an eCommerce, it’s impossible to succeed without being data-driven from the core. Only relying on the information about the clients’ buying behavior, their goals, and needs, a small business can make its way in the competitive marketing world.
The whole point of collecting and researching business marketing data lies in need to create a portrait of the target customer and adjust the entire business to cater to it. Since machine learning algorithms are a massive help in terms of sorting the most valuable marketing data, there’s no reason why a small business might still go without benefitting from the available tools for boosting their marketing efficiency.
The abundance of the user data makes it confusing to choose the metrics to focus on. Therefore, here’s the list of the most vital marketing data parameters to rely on.
Average Total Revenue Per Customer
Seeing the figures, you can trace the buying ability and the product relevance for the customer to decide whether it needs to be developed or changed.
Percentage Of Converted Leads
Just like the amount of traffic, the number of leads has almost no importance. Dividing the overall number of leads by the converted ones, you can see if you’re attracting the right audience the right way.
Percentage Of Repeat Business
This piece of data gives you an insight into the level of customer interaction you’ve developed. If people tend to revisit your website making purchases over again, keep the customer management up this way.
Cost Of Acquisition
As more evolving businesses operate online, social media advertisements are the main acquisition way. By comparing the cost of ads to the number of your followers, you can see if the ads are paying off.
Bounce rates basically show the clickability of your website. But the number of clicks is nothing if purchases aren’t growing. That’s why keeping an eye on a steady bounce rate is necessary to avoid the pink glasses effect on your eCommerce.
Outsourcing Data Management vs. In-House
Since the necessity of data management for small businesses was clearly outlined, here comes the question about who should deal with data optimization and analytics. Outsource data management has proved efficient, but what are the in-house option benefits? Let’s dig a bit deeper to find out.
Why Consider Outsourcing Data Management?
No company can survive without building a solid network, which later becomes a reliable supply chain. Having an accessible vendor outside ready to consult you on data management and its beneficial usage is a valuable asset. Data management outsourcing allows small businesses to free their hands for more specific company boosting tasks and to avoid spending sums on in-house equipment, data management essentials, and their regular updating. Another obvious advantage of keeping a data center out of the company is that distancing your data will require its duplication and decrease the chances of vital information losses.
The only pitfall when outsourcing data management is the choice of a wrong supplier. Thus the hiring process should not omit credibility research, annual continuity percentage, and technical skills testing.
Why Go For In-House?
Building a strong, experienced data management group of specialists who take care of the data analytics and protection would be a solid core of any evolving business. Moreover, maintaining in-house data management will generate higher clients’ trust and wider open doors for effective infrastructure building. So even though keeping your data center in-house and ignoring data science outsourcing is considered a burden, gathering a team of professionals under one roof is impressive.
However great it may be to hire a data management crew to work for you permanently, small-scale businesses should not rely on this perspective as its maintenance is unlikely to be cost-effective.
Regardless of all the pros and cons of data management strategies, no company should consider running without data reliance as such a misstep may cost a business its future.
5 Steps For Efficient Data Management
Data is not something new to our lives. We’ve been taught how to manage data since school, trying to avoid messy paper piles and confusing lecture notes to be able to find the necessary information quickly. Digital data management is not entirely different from that experience. Here’s the 5-step guide to enhancing business by taking proper care of your data.
Keep It Simple
Digital data files should be managed just the way paper documents are - using marked folders. The key is to arrange them clearly, name accordingly, and preserve the chosen method specific data is sorted. For this purpose, data management tools, databases, and platforms are often used.
Avoid Big Data
Business data management is not about big data. Actually, it’s more about avoiding huge unsorted tons of information. Such databases would be perfect for machine or deep learning, but not for growing business profits, eliminating messy voluminous data pieces.
Clear The Trash Can
Redundant data does not delete itself, so to avoid piling up irrelevant information, you’ll have to update and clean the outdated data yourself. Moreover, storing redundant data may lead to company losses due to false statistics and bad analytical outcomes.
Estimate Your Data
The ability to distinguish the valuable data from the incidental is already half of successful data management. It’s important to note that even though demographic data prevails, how people interact with your business is much more significant. Thus focus on analyzing the qualitative data instead of a quantitative one.
Visualize Your Data
Few people like sitting hours in front of data lists, trying to figure out the business tendencies, and read clients’ behavior through the lines. Visualizing the data, creating charts and graphics is probably the most productive way of using the information. It’s easy to get your point across to the team without drawing verbal images.
The Bottom Line
Data management for small businesses is now an unavoidable must. Even though the process and intelligent automation take place in keeping, defining, and protecting the valuable information, it’s still not an utterly robotic process. Efficient data management strategy is not only about keeping the information in order but knowing how to use it for maximum profit and long-lasting marketing benefits. That’s why the steady growth and competitive future of any enterprise are now impossible without being quality data-driven.