How can data analytics improve your business operations?

he use of analytics as a means of streamlining operations and improving processes is something any business can benefit from…

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A data dashboard showing bar and line charts

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Using data and technology to transform the operations of your car park

The use of analytics as a means of streamlining operations and improving processes is something any business can benefit from. With the availability of data capture technology increasingly available in this day and age, leveraging customer data and putting it to good use makes plenty of sense. However, certain businesses might not necessarily be aware of how much the analysis of data can have such a positive effect on their organisation’s operations.

For a start, it can be confusing knowing which kind of data is going to be beneficial to your business. Additionally, some organisations might be unfamiliar with the ways in which data findings can be implemented in their processes. In this article, we’ll delve deeper into the ways analytics can be leveraged across differing sectors, as well as the different classes of data analytics that you can use to improve the management and operations of your car park.

 

What are the different types of data analytics?

Descriptive analytics

The most common type of data analytics, this category is able to summarise raw data and convert it into a form that people can easily understand. It’s crucial in revealing key metrics and measures within businesses of any kind, as they can describe in detail events that have occurred in the past. Strong visualisation tools enhance the message of such analytics.

 

Example: A monthly profit and loss statement or demographic information on customers.

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Diagnostic analytics

This subset of analytics allows analysts to explore issues in greater detail in order to arrive at the source of a problem. By looking at past performance, they’re able to determine what happened and why. In certain types of businesses, descriptive and diagnostic analytics work particularly well together.

Example: Social media marketing campaigns, where the number of posts, mentions, followers, fans and more can be assessed to see what worked well and what didn’t.

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Predictive analytics

Predictive analytics allows businesses to forecast trends based on current events, whether it’s the probability of something happening or the time it could potentially happen. Through the use of variable data, it allows businesses to make better decisions, so predictive models are some of the most important that can be utilised across a number of fields. Effective and accurate predictive analytics can also complement business activities such as business acquisition, planning and budgeting.

Example: Done properly, predictive analytics can be used to support sales and marketing.

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Prescriptive analytics

At its core, prescriptive analytics is a combination of all three previously mentioned types that helps analysts determine the best course of action to take. It’s often considered the most valuable kind of analysis, providing results and recommendations for a given process’ next steps.

Example: Sat-nav systems helping you choose the best route home and taking into account the distance of each route, the speed at which one can travel on each road, and information on current traffic constraints.

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What impact does analytics have across sectors?

Operational efficiency

If you’re looking to streamline processes and maximise profits, then data analytics can help in a big way. For one, it can identify problems before they occur, reducing the actions needed to correct them and saving on time as a result. Companies can then see which operations have yielded the best overall results under various conditions, as well as the operational areas that have room for improvement – driving down costs and improving the business’ bottom line.

In identifying inefficiencies, businesses can ask themselves what the cause of the problem was, the reasons for it happening, predictions for the future, and what the next course of action will be.

 

A greater understanding of customer base

Identifying the customers who are more likely to come back again and again means you can strengthen what makes you so attractive to them in the first place. Fostering a long-term relationship with customers increases value and lets you improve on your business operations’ successes if necessary.

And the type of customer you identify plays a part in increasing your customer base by knowing who to aim for. Analysing your current customer’s buying habits provides information on who they are, why they’re choosing to do business with you and when they use your facilities.

Of course, it is important to consider GDPR restrictions and implications when collecting customer data. This should inform your process of offering an opt-in choice for customers, clarifying the benefits they could receive.

When it comes to car parking, data analytics provide a more comprehensive view of customer activity. Vehicle movement allows you to glean a huge amount of accurate, intelligent insights about customers, including repeat visits, heat maps of the most popular dates and times and average duration times. Daily, monthly and yearly comparisons also become available, with trends in capacity and utilisation providing important information on where things can be improved upon.

Data collection also helps you to benchmark your car park against competitors, similar industries and local neighbours. This benchmarked data can help you gain a deeper insight into seasonality, capacity and average prices. Using the available data, car park owners can make an informed decision on pricing and strategy – reducing examples of empty spaces, and improving the profit margin.

Services such as Glyde can crunch live occupancy data and make it accessible to motorists looking for available parking nearby. Not only does this provide a true reflection to the landowner of their car park activity and drive up revenue by allowing people to rent surplus spaces, but also attracts new customers to the business as a whole – all from robust occupancy data. Without the statistics in place, it is difficult to truly represent anticipated and actual occupancy levels.

Additionally, if your business has a large customer service element, then the real-time reporting that data analytics affords can improve efficiency in this area markedly. Reporting allows customer service staff to know information about customers while interacting with them. That means less time keeping them on hold, and more time having access to the questions that they have already answered – cutting down on call and hold times for a more improved experience.

This data ensures your team is well-equipped to target new customers and retain existing ones. All contract-end dates, breaks or upgrades can be acted upon in a swift and timely fashion. Additionally, high-churn individuals or groups can be identified and targeted appropriately.

 

Fosters a data-driven culture

Placing data at the heart of everything the business does, from leadership down ensures everyone has a greater understanding of how data helps to drive organisations forward. Ensure everyone knows the importance of data in their role by properly integrating it through data-driven decision making.

Partnering with service providers who specialise in data capture and analysis could significantly benefit your business, helping you identify opportunities as soon as they present themselves.

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