Real-time data is fascinating. It’s possible to track all kinds of metrics as they change before our eyes. For example, we can see how much money is spent, second by second, across various industries. As you may imagine, that can have a considerable knock-on effect on sales intelligence.
However, to better understand how sales intel can benefit from RTD standards, we need to consider the broader definition.
What is real-time data?
Real-time data is information made available to users as and when it arises. A database of real-time data, or RTD, is constantly updating. Therefore, users can expect data accuracy regardless of how they may use it. With big data only expanding, understanding its growth ‘mid-flight’ is hugely beneficial.
Raw data, collected in real-time, is collated from multiple different sources. This may include aggregates from publicly available marketing information, social media records, and shopping behavior. This data is typically gathered in a central database or warehouse from said disparate origins.
Before analysis, data is cleaned and arranged for relevance. However, with real-time collection and analysis, there is an emphasis on a progressive stream. This process of data collection, made possible through machine learning and advanced tools, allows information to keep evergreen and relevant.
Real-time data formatting is rarely recommended, as it may slow down the gathering process. However, doing so may help to improve processing speeds in time to come. Users of RTD will, typically, have a base catalog or template in place for data to flow into. Crucially, given that this is the management of a literal, ever-growing data stream, there must always be space available.
In practice, hybrid cloud setups allow businesses to manage ever-building data feasibly. Flexible storage in the cloud can ensure data analysis systems are always prepared to accept new information and overwrite it.
RTD analysis is a never-ending, continuous process. Analytics close to the heart of this process may include ad-hoc forecasting, diagnostics, and problem-solving. By watching data change in real-time, problem solvers can build solutions ready to pivot on demand.
Why is real-time data important in sales?
Real-time data can help users and agents get ahead of the curve when applied to sales intelligence. Specifically, RTD intel can enable sales teams to watch sweeping trends and changes as and when they occur. Businesses can then plan for changing consumer behavior, for example, without wasting time developing long, sprawling reports.
Real-time data also allows sales professionals to watch changes take effect. For example, by changing a funnel or adjusting pitch strategy, analysts can watch interest peak or drop. There may, for example, be a shift in expenditure, website visitation time, or conversion through cold calls.
This allows sales teams to adjust and adapt quickly. Data is available in minutes rather than waiting weeks or even months for reports on strategy changes. Analysts can set their own time parameters before further adjusting strategies.
Gain an Edge Over the Competition
RTD allows sales agents to gain an ‘edge’ over competing businesses. While long-term forecasting may still hold water in some industries, RTD inspires immediate action. Seeing data evolve - and answer questions ad-hoc - can allow for faster resolutions to broader problems.
RTD is useful in a wide array of different sales metrics, too. Pooling from web activity, for example, agents can see where people are visiting online content from (search, socials, etc.). It can also help identify ‘trending’ items and niches. This can help marketers to plan and target sales events, for example.
It’s also helpful in building sales and generating leads across various industries. RTD can prove crucial for tracking e-commerce behaviors and attitudes towards SaaS. It can also deliver insights into competing brands, products, and sales strategies elsewhere.
How do sales intelligence and real-time data benefit your business?
The average consumer demands efficiency and quality in service in equal measure. The rise of the app age has created a thirst for immediate support. As such, sales teams need to move just as quickly as the apps and platforms consumers are accustomed to. Real-time data provides agents with direct insights, allowing them to react swiftly and plan on the go.
This, in turn, can lead to more satisfying customer engagement. CRMs using RTD, for example, provide users with immediate answers to common pain points. For example, a sales intel suite benefiting from RTD can help agents tailor personalized calls and pitch better. Real-time insight can assure customers that sales teams and service reps are always up to speed.
Beyond customer service, RTD will also allow sales teams to take instant action on time-sensitive matters. Sales dips that may potentially grow into droughts are easily handled at the crisis point. Continuous data, continuously monitored, presents opportunities for growth and crisis aversion that may otherwise be easily missed.
The knock-on effect from here is cost reduction. Sales droughts and problems immediately resolved through real-time analysis prevents unnecessary expense. With real-time information, closer personalization in sales calls can encourage greater lead conversion. In addition, real-time monitoring can lead to opportunities where businesses can find new, competitive gaps in the marketplace.
The argument against this final point may be that competing businesses, too, use RTD. However, real-time information is vast and sprawling - and it’s the parameters specific to your company and customers that matter.
Keeping your sales strategies up to speed with real-time data is a must. In the New 20s, data will continue growing thicker and faster. With access to databases of real-time information to help boost your own sales intel, your insight potential will skyrocket.
Of course, sales intelligence is never a one-size-fits-all concept. Metrics, parameters, and goals will differ from business to business. But, now is the time to embrace real-time streams of data. If you’re still building monthly reports - and not from minute to minute - you may just be missing out.
Topic: Sales Intelligence