This post is a guest contribution from Alexa Lemzy, content manager at TextMagic.
Collecting data is a vital part of improving your business model. By itself, however, this data is not always useful. Turning the facts you collect into relevant information your business can use is the next step toward data-driven decision making. Effective businesses know how to collect the right kinds of statistics and how to extract useful analysis from that data.
What is data-driven decision making?
Data-driven decision making involves collecting business statistics based on measurable goals,
analyzing them for insights, and developing changes and new strategies for your business using those insights. This enables your business to move forward with goals and new approaches based on facts and data analysis instead of guesswork or gut feelings.
Collecting data in business processes
One of the keys to effective data collection is making it a part of your routine business process. In almost every part of a business, there is significant potential for collecting data, so it’s important not to waste time and resources collecting data you can’t use. Instead, consider the goals you are trying to achieve, and focus on gathering evidence related to those goals.
Collecting and analyzing intelligence from different parts of your business can be a significant drain on your time. It also creates a lot of potential for human error. Instead of relying on manual work, use a business platform to automatically track key metrics and log feedback from any source. This reduces the amount of repetitive data entry tasks you need to complete, and it also enables you to easily collect and work with figures from across your business.
It’s important to use collection tools that integrate with systems like Salesforce. For example, Cadence Bank uses FormAssembly’s Salesforce integration to collect account and application information. This has enabled the Cadence team to easily convert files and processes from other banks during a merger.
Collecting customer data
Some of the statistics you need may already be available and accessible. For example, if you know how many subscribers your service has each month, you can calculate other numbers like user growth, retention, and churn. Other forms of data, however, require specific collection tools and methods.
Sign-up and cancellation forms
Including optional fields in your sign-up and onboarding forms allows customers to provide extra information. You can collect information about their specific needs, how they found your business, and other details in order to categorize your audience and understand them better. Similarly, account cancellations provide an opportunity to collect vital information that you can use to reduce customer churn in the future.
Customer surveys and feedback
Customer ratings and feedback surveys can provide quantifiable data on customer satisfaction rates. When you’re asking users for more in-depth answers to your questions, a text analysis tool can help you process responses much more efficiently.
Text analytics
Text analytics tools use Natural Language Processing (NLP) to understand and analyze written text such as customer emails, support tickets, or comments on social media. Reviewing and categorizing each customer contact individually is an immense task, but text analytics tools can automatically turn responses from multiple sources into measurable evidence.
Extracting information from customer data
The next step is to use your figures to draw conclusions on strengths and weaknesses in your business model. It is important to consider these statistics in light of industry standards and to compare your data against your closest competitors. This will enable you to make more informed decisions when planning new projects or business changes.
These questions will help you focus your data analysis on the most relevant metrics:
- What do you want to learn from your analysis?
- Which Key Performance Indicators (KPIs) can be used to quantify the answer to your questions?
- Which factors does your investigation consider, and which does it ignore?
It is important to analyze every metric that could be affected by the area you are aiming to improve, or the new project you are planning. Failing to consider a secondary factor could lead to you making changes with little impact. Even worse, you could negatively impact the area you were trying to improve.
You should also look at how each part of your business impacts individual data points in order to understand how your business as a whole is performing.
Using insights effectively
To put insights into action, you need to ensure widespread adoption with the changes you propose. While it is important to keep all of your employees informed, try not to overload staff with irrelevant information. Consider which parts of your business will be involved with a project or change in business processes, and to distribute the relevant details to the right people.
Creating graphs, charts, and other visualizations will make it much easier for employees to understand the data behind your decisions. This will also enable you to back up your proposals with clear evidence and reasoning.
Conclusion
Gathering useful data is an important part of any business. Remember, however, that collecting data is only half the work, and analysis is needed to extract the information your business can act on. Organizations need to be able to identify useful data and analyze it in order to make improvements.
Alexa Lemzy is the content manager and customer support person at TextMagic, a mass texting service. She is passionate about mobile marketing, customer experience and communication. You can reach her on Twitter.
