3 Ways Predictive Analytics Pull In Huge Returns for Sales and Marketing Orgs

3 Ways Predictive Analytics Pull In Huge Returns for Sales and Marketing Orgs

3 Ways Predictive Analytics Pull In Huge Returns for Sales and Marketing Orgs Can business be predicted?

Running a business is often compared to gambling. Instinct is the word for business acumen, and chance the most powerful factor that determines success or failure.

Whoever first came up with this analogy had business all wrong.

The truth is, business can be predicted. The outcome of business can be forecast, much like the weather station warns us of an upcoming cyclone. This is possible through predictive analytics, a science that identifies future scenarios by reading, processing and analyzing historical data.

Fred Shilmover, CEO of analytics firm InsightSquared, has spoken of predictive analytics as a “three-part formula.” According to him, what predictive analytics does is looking back at the past, understanding the present, and using the connection between the past and the present to infer what the future may be.

The historical data, or the past, intensely scrutinized in predictive analytics are culled from various sources, and most of these are born and bred by the internet. Data can come from digital marketing tools, social networks, and other avenues that help businesses gain insight into customer behavior.

What predictive analytics does is make sense of the overwhelming amount of data available to businesses today. Once properly processed, the information will provide businesses concrete basis for strategic decisions that will bring greater profit margins.

Increased profit is a certain future scenario for businesses that use analytics. Jonathan Gordon, one of the authors of the book Big Data, Analytics and the Future of Marketing and Sales, wrote in Forbes.com:

“Those that use Big Data and analytics effectively show productivity rates and profitability that are 5 – 6 percent higher than those of their peers.”

All businesses stand to profit from using predictive analytics, but the ones that make the most out of this science are sales and marketing firms. These agencies make a living by guiding businesses into the future. Marketing companies study, analyze and recommend strategies to businesses to help them grow and earn more.

With predictive analytics, the work of sales and marketing agencies just got easier, more accurate, and ultimately, more profitable.

Predictive Analytics Narrows the Target

The amount of information available on the internet is unbelievably huge. Every click, like, post, retweet, comment, email—all of these become part of statistics that may or may not show how well a business is doing. Sifting through tons of information may take hundreds of years but thanks to predictive analytics, data can be sorted and broken down to useful bits that humans can understand.

These useful bits are the parts that sales and marketing organizations look for. These bits are the golden opportunities that businesses sometimes fail to see. These can be spikes in sales during a specific season, a demographic that responds well to a marketing strategy, a behavioral pattern common to customers, or a growing demand that seem to fall under the radar.

Consider the success of CVS Health in implementing a call center pilot program that used analytics. CVS health used a tool by Mattersight that matches the callers and clients based on behavior. By dividing clients into six behaviors, the company was able to make calls faster and more productive.

Knowing specific information helps marketing agencies hatch effective plans for businesses to improve operations, catch more customers and retain their loyal clients. Demand forecasting can also be possible with predictive analytics, a game-changer for starting businesses looking to carve their niche within the market. With accurate and data-based scenarios, agencies can make predictions about the market with confidence.

E-commerce businesses like Amazon and Netflix capitalize on predictive marketing analytics to reach viable clients at opportune times. Businesses that transact with customers online have the advantage of accessing personal data through search engine analytics. Such information allows businesses to target certain customers with personalized ads and product suggestions. Through machine algorithms, these promotional materials are offered to different customers at different times of the day, depending on the user’s pattern.

In addition to accuracy, predictive analytics also cuts the time and effort required of sales and marketing agencies to study a business and identify opportunities. This does not mean, however, that predictive analytics does all the work. Human insight into the data is still needed to make the right recommendations.

With predictive analytics, sales and marketing firms can be more efficient in data mining and data analysis. They can cover more ground in less time, and come up with better business plans backed up by concrete data. All these advantages ultimately add to the credence of sales and marketing agencies, raising their status in the community, and of course, the price of their services.

Predictive Analytics Prevents Mistakes

Think of predictive analytics as a cheat in Minesweeper. Predictive analytics identifies where the bombs are hidden, letting you tiptoe your way to victory. Applied to a business, this means that predictive analytics keeps you from making the wrong moves.

The wrong moves, in the world of business, translates to losing money.  It could be spending on the wrong demographic, increasing the campaign budget of the wrong products, or pursuing the wrong revenue model. These mistakes drain money from businesses and lower the margin of profit.

It is the job of good sales and marketing organizations to advise businesses against these costly ventures. Through predictive analytics, agencies will have a better grasp of what business model works and what fails. Agencies can identify the red flags in business practices, and point out future mistakes that the current direction of the company may be heading to.

For example: A pitfall of conventional business planning for a retail store is using the previous year as the baseline for new business goals.

Predictive analytics will throw this idea out the window, and show that plainly looking at last year’s performance is not enough. One has to factor in demand for the goods, availability (supply) and lost sales. Lost sales in this respect do not just refer to days without sales. Instead, it refers to sales that could have been made on days when demand was up but supply was zero.

When things seem to be going well, the logical step is to look for the mistakes that can bring the business down. If sales and marketing orgs can alert businesses on bad business practices, revenues will surely grow for both parties.

Predictive Analytics Improves Relationships with Customers

In a survey conducted by NG Data, business executives were asked: what is the first business problem  solved by predictive analytics?  Each reply was unique, but all the answers had one common element. All of them agreed that predictive analytics helps companies better understand their customers.

One of the survey’s respondents, Nathan Gnanasambandam, Ph.D. works at Xerox as a Senior Research Scientist at the PARC’s Big Data Analytics Lab. His answer explained how customers and analytics are related. He said:

“Customer service is a top priority as well as a tough business challenge for every business. Data analytics is a key tool that can be used to not only provide better customer service – but also deepens customer relationships.  Predictive analytics can pay a major role in the customer experience decreasing – and in many cases–eliminating customer issues before they even occur.”

Insight into customer behavior is indeed the most obvious and most important perk of using predictive analytics. Analytic tools delve into personal accounts, social media platforms, and other venues, picking out personal information and analyzing it. Once aggregated, these data paint a picture of the customer—his/her taste, behavior, personality, and ultimately, his consumer journey.

So how does data science improve customer relationship management (CRM)? Insight into the customer psyche enables businesses to better relate to their customers. Businesses can customize their CRM strategies to suit customer types. Data can help in determining the most fertile market, and isolate the most inactive. Analytics can ultimately help businesses create personalized transactions to get closer to their clients, and earn their trust.

CRM is vital in client retention and reputation management. Regular interactions with customers provide a wealth of information, allowing businesses to delve deeper into their behavior and motivations for patronizing a business.

The L’Oreal  Group is already using analytics to promote their brand. The cosmetics giant monitors social media posts, tweets, and product reviews about the brand, and engages users in raising “brand awareness.”

Predictive analytics gives sales and marketing orgs a vivid description of the ideal customer. This piece of information guides these agencies in formulating market plans on how to turn prospects into customers. Every part of the business plan revolves around this information, proving the importance of analytics in creating business models anchored in reality.

Predictive analytics makes great things possible for businesses. It gives businesses a glimpse into the future, inspiring the right strategies towards bringing greater returns.  It profiles customers, studying what they want, need and how they can be wooed by businesses. It connects random events and factors, giving businesses the full picture of the current situation.

Sales and marketing orgs today are fortunate to have access to analytics tools to process the abundant information available online. Such software and programs have automated the processing of trillions worth of information. They have sped up and made the market study and research more accurate and precise.

In this day and age, data flows from one source to another in an instant. Sales and marketing orgs are already cashing in on this wealth of information, thanks to the help of predictive analytics.

Data science has literally turned the heads of businesses and set their eyes on the future. With the right set of data, there is no need to rely on chance to make businesses grow. All you need are the right tools, and the future will be clear.

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