For data-driven marketers, real-time analytics are increasingly critical to creating value for businesses and clients. This isn’t just another Big Tech buzzword — the effective real-time analysis of customer and marketing data can provide a serious boost to your revenue. Business owners and managers who analyze their data in real-time will make better, smarter decisions backed by the most up-to-date info.
The bottom line: Marketers who stay ahead of this trend will reap big dividends for both their businesses and the clients they serve.
Two different datasets
Real-time analytics revolves around two different types of data: Customer data and operational data. Before embarking on your journey through the wilds of Big Data, it’s important to carefully consider how these two datasets pertain to your business, and to identify the most relevant key indicators from each. Properly tailoring your approach to real-time analytics is key to increasing your marketing performance and trimming expenditures.
Real-time analytics for customer data involves using both individualized and industry-wide customer data to inform your approach when interacting with a customer. Gathering customer data across multiple channels will paint a picture of their wants and needs, and how they discovered your business. This data can then be used to better manage customer relationships, and to provide them with targeted offers and enticements to keep them loyal.
Say you’re an Internet service provider, and a customer calls with the intention of canceling their subscription. Real-time analytics can be used here to calculate the attrition cost of losing this customer, and to evaluate their prior purchases. With this data at the ready, a sales rep can decide whether to make a targeted offer to convince the customer to stay.
On the other hand, operational analytics are more of a top-level measurement of the cost and effectiveness of your marketing efforts. This covers data like the ROI on a PPC campaign, which can help your marketing team tweak and adjust your digital ad buys on the fly as relevant performance data comes in. With real-time monitoring of your various ad channels, you can at any time know which channels are driving the most business, and tailor your approach accordingly.
This all sounds pretty good so far, but how does this actually apply in the real world, where brick meets mortar? Let’s look at some examples that cover these differing datasets.
Tenzo uses real-time analytics to take restaurants to the next level
In the UK, the London-based startup Tenzo aims to shake up the restaurant business through its unique application of real-time analytics. By providing moment-to-moment data on how a restaurant and staff are performing, Tenzo empowers managers to make informed decisions around staffing, ordering supplies, forecasting future demand and even determining which menu items should stay or go.
“The amount of data that restaurants generate is exploding and technology is fragmented. This makes it hard for restauranteurs to make informed decisions,” Tenzo co-founder Christian Mouysset told TechCrunch. “We automate this thereby reducing the error rate and the time spent preparing [data] and make them available in an easier format to digest.”
Lyft is ready for Prime Time
You might be more familiar with this use of real-time analytics: The “heat maps” in ride-hailing apps like Lyft helps drivers locate areas of high customer demand. Heat maps identify areas where there’s more demand for drivers than available cars on the road, and then overlay that info on the driver’s in-app map in real-time.
This allows drivers to focus their time on high-volume locations that are most likely to incur surcharges — ‘surge pricing’ or ‘Prime Time,’ as it’s lovingly known — meaning more revenue for both the driver and the company.
Microsoft goes head-to-head with Salesforce
In a move targeted directly at Salesforce’s dominance in the CRM space, Microsoft is set to unveil a new suite of features for its Dynamics 365 sales software, which puts to use the data acquired during the company’s recent purchase of LinkedIn. Their centralized AI software promises to help agents close sales by leveraging calendar, email and LinkedIn data in real-time.
“I want to be able to democratize AI so that any customer using these products is able to, in fact, take their own data and load it into AI for themselves,” explained Microsoft CEO Satya Nadella.
CallRail in the Copilot seat
To get a sense of how real-time analytics applies in a sales setting, look no further than the Copilot call tracking solution by CallRail. As calls come in to tracked phone numbers, Copilot will display relevant data for that lead in real time, such as the status of previous calls, their prior web and mobile activity, and even recordings of prior phone conversations.
Sales teams can use this info — alongside CallerID and any relevant data from integrations — to make smart, informed choices and quickly address your customers’ needs.
Putting your real-time data to work
Every business has their own unique needs and goals, which means that no application of real-time analytics is going to be the same between two organizations. The first step in putting your data to work is figuring out which metrics and performance indicators are most critical to your organization. From there, you can begin monitoring those indicators, and using them to measure the health of your business and marketing.
This means you’ll need to find the right platform or CRM to store and aggregate your data. Learn more about the intersection of real-time analytics and call tracking.
It’s also important to remember that analytics can only show what happened in the past — they cannot predict the future. Having the best, most relevant data at your fingertips helps you make the best possible choices, but it can’t make those choices for you!
With the right mix of hard data, intuition, expertise and real-time insights, you’ll be equipped to make truly winning and impactful decisions for your business.