Tag: predictive analytics in 2020

customer analytics in retail

Weekly Round-up: A Storyboard on the Benefits of Predictive modeling Techniques

LONDON: Quantzig, a leading analytics services provider, has announced the release of their latest storyboard on predictive modeling techniques and how it can help businesses in proactive decision making and pre-emptive planning.  With the availability of data in enormous volumes, it has become quite difficult for businesses to rapidly identify, objectively evaluate, and confidently pursue new market opportunities.

By using predictive modeling techniques, companies can enhance decision making and gain the ability to optimize, direct, and automate decisions, on demand, to achieve defined business goals. By applying predictive analytics models, businesses can not only better manage the present, but can also improve the probability of success in the future. In doing so, such companies become predictive enterprises.

The goal of predictive modeling techniques is to turn data into information and information into insights.

Quantzig’s analytics solutions have helped more than 55 Fortune 500 companies to make data-driven decisions and augment revenues. Below, we have rounded up some of Quantzig’s recent success stories for this week and have also highlighted ways in which predictive modeling techniques have helped businesses to become market leaders.

#1: Predictive modeling techniques improved 85% accuracy in demand forecasting: Providing seamless customer experience and complete customer satisfaction is a challenging task for any business. Don’t you agree? But predictive modeling techniques can help as it helped one of Quantzig’s clients. By utilizing predictive modeling techniques, companies can conduct analysis on historical information on sales, products, and inventory levels. Furthermore, it can reduce irregularities and streamline order management, resulting in better demand forecasting.

85% accuracy in demand forecasting achieved by a leading computer hardware manufacturer through predictive modeling techniques

#2: Predictive modeling techniques precisely forecasted the roll-out of a new initiative: Predictive analytics models are the best way to improve business operations and predict future trends. This is clearly evident in Quantzig’s latest success story, where the client managed to make accurate predictions about the success and failure points of their new initiative. Moreover, it enabled optimal budget allocation.  

Leveraging Predictive Analytics to Forecast the Roll-out of a New Initiative for a Leading Grocery Retail Chain

#3: How can clustering algorithms uncover relations between invisible variants? If you are looking to upsell your products, this predictive modeling technique can certainly help. Clustering algorithms use data mining techniques to find out the relation between different invisible variants. Furthermore, this helps businesses to obtain desired outcomes.

Top 3 Predictive Modeling Techniques That You Must Know

#4: Predictive modeling techniques optimized inventory management: Optimizing inventory for better customer service is very essential for the success of any business. By leveraging predictive modeling solutions, companies can build better inventory and can discover capabilities to drive continuous market excellence. Furthermore, predictive modeling techniques can be successfully implemented, either independently or in tandem, to offer actionable insights into the performance of the inventory.

Improved inventory management achieved by a leading oil and gas company through predictive modeling techniques

#5: How predictive modeling techniques can boost business outcomes? : Changing customer dynamics poses critical challenges before businesses such as managing customer demands. Don’t you feel the same? This is where predictive analytics plays the role of a savior. By leveraging predictive analytics solutions and utilizing predictive modeling techniques, companies can deal with a humongous set of data, which can aid decision-making.

3 Ways Predictive Analytics Solutions Can Help Businesses Derive Successful Outcomes

#6: Utilizing predictive modeling techniques to boost customer retention dramatically: Managing the huge amount of customer data is not an easy task for businesses and we understand that. This success story is an excellent example of that as one of our clients faced the same issue and approached Quantzig to leverage its expertise in offering predictive analytics solutions to reduce customer churn rate.  Also, our predictive modeling techniques proved beneficial for the client in integrating traditional and digital data sources to correlate the data and identify potential churners.

Telecom company improves customer retention through predictive churn model

#7: Why you can’t afford to ignore predictive modeling techniques?  No matter which industry you are in, retail, transport, or healthcare, you cannot ignore the importance of predictive modeling. It helps you to gain a comprehensive understanding of the market trends, customer behavior, or competitor’s approach. Furthermore, by utilizing predictive analytics models, companies can easily track the volatility of different categories, brands, and products. This can result in better business outcomes.

Is Predictive Analytics All Set to Drive Success in the Transportation Industry?

#8: Predictive modeling models identified inefficiencies and improved ROI: Analyzing customer lifecycles to devise better marketing strategies and improve customer service is one of the common issues that every business faces, so don’t be surprised if you are facing the same challenge. If you have a proper predictive modeling technique in place, you have nothing to worry about. A leading firm in the healthcare industry was facing the same issue but witnessed a great change in their approach to risk assessment after leveraging Quantzig’s predictive modeling solutions. Moreover, it reduced inefficiencies drastically and improved their ROI.

#9: Predictive modeling techniques enhanced fraud detection and customer satisfaction: For some businesses, anticipating fraud risk is a herculean task. This impacts their customer service  and the customer ends up having a bad experience. So, for such companies, utilizing predictive modeling techniques is a necessity as these techniques can help anticipate potential suspicious claims and fraud risks.

Claims predictive analysis delivers reduction in frauds and enhanced customer satisfaction for insurance company

#10: How can predictive modeling increase accuracy and improve efficiency of marketing strategies?: Accuracy in forecasting the impact of several factors on the business outcomes is essential if you want your business to grow. Predictive models, in this context, hold the key to success. These models have the potential to assess and predict the performance of different components and their tentative impact on the future of the business. Furthermore, this can allow companies to make smarter decisions and exit declining markets.

How Healthcare Industry is Leveraging Predictive Analytics to Improve Patient Outcome

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3 Ways Predictive Analytics Solutions Can Help Businesses Derive Successful Outcomes

With the shifting key values of every industry from customer-focused to customer-centric, there is an immense growth in data and information. This has changed customer dynamics and as a result, every business is facing numerous challenges such as market uncertainties, driving efficiency, and effectiveness in their marketing productivity, immense competition, customer demands, fraud detection, and risk management.

Many businesses across all industries, in order to cater customer demands, are trying to utilize the data that their customers leave behind while interacting with the company. Harnessing this pool of data can offer several benefits to organizations. However, many companies still have not realized the importance of data mining and have not gone beyond gathering and storing their data. Although it is difficult to deal with an unstructured set of data by leveraging predictive analytics solutions businesses can fetch optimum results from such data. 

At Quantzig, we understand the impact that predictive analytics solutions can have on your business. And to help companies derive actionable insights from large and complex data sets, our team of experts has highlighted three important ways in which predictive analytics solutions can help in managing large volumes of data and setting up analytical frameworks to derive real-time insights that facilitate more informed and wise decisions.

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4 Tips to Get Your Oscar Predictions Right: Is Predictive Analytics the Answer?

The Oscars, also known as the Academy Awards, is a set of 24 awards for artistic and technical brilliance in the American film industry. This year, the 90th Academy Awards broke many records – crowning the oldest Oscar winner ever and the first black screenwriter for the best original screenplay, selecting a science fiction film to win top honors, and picking a Chilean film as the best foreign language film. But with this year’s Oscars already out of the way, most of us are already on the lookout for ways to get next year’s Oscar predictions right and profit out of the Oscar ballots that we find ourselves addicted to. A recent trend that has been picking up some traction among betting enthusiasts is that of predictive analytics. Recent evidence suggests that the day is not far where we can predict the outcomes of such award ceremonies and other events accurately. So, how exactly can you get your Oscar Free demopredictions right using predictive analytics?

  • Firstly, you have to look at a lot of factors which signals how the movie was received by the audience, such as its financial performance and likeability.
  • Next, cross-analyze such factors to generate accurate predictions.

Sounds complex? Fret not, here’s a simple list of factors that you have to pay attention to get your Oscar predictions right:

Buzz and fanfare

To get Oscar predictions right, take a movie’s relative buzz along with its fanfare is taken into consideration. In most cases, companies analyze which movie was the most talked about in social media platforms and the film that received the best review. Prediction algorithms are built on the belief that the public’s opinion and attention influences the votes. For the calculation part, data analysts take into account Google search volume, IMDb ratings, tweets, and other similar ratings of the movie to create an aggregated score to predict the success rate.

Prior awards

Another way of getting accurate Oscar predictions is to analyze all the previous awards the movie has earned. For instance, numerous awards ceremonies take place before the Oscars, including Golden Globes and Screen Actors Guild Awards. Since such awards are also likely decided by people who cast votes for the Oscars, it makes sense to factor in such awards to predict movie success. The higher the number of previous awards won by a particular movie, the higher its chances of winning the Oscars.

Financial performance

Although many artists value the quality of their art with the number of awards won by it, studio and media houses rely more on the amount of money it brings in. Spending millions of dollars in making a movie should give them fruitful results. As a result, financial performance matters and to a certain extent influence the votes. Consequently, many prediction models take into account the box-office revenue generated by the movie in relation to its overall budget to improve the success rate of their Oscar predictions.

Critic reviews

The closest thing to the voters of the Oscar awards are the movie critics. Even the public and fans eagerly wait for critics’ reviews before watching a movie. Although critics and publications don’t possess the sole voting rights, they can certainly influence the public and industry leaders. As a result, predictive analytics models factor in critic reviews to improve their Oscar predictions.

To know more about how predictive analytics can help in Oscar predictions:

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The Future of Predictive Analytics – Vision 2020

Predictive analytics has recently gained momentum as organizations seek market and consumer insights to assess the value of their businesses in the future. Organizations across several industries such as retail and consumer packaged goods and healthcare are already leveraging the benefits of predictive data analytics to drive profitability and improve operational efficiency.Predictive data analytics has helped retailers and marketers understand the consumer buyianalystng pattern, follow the clickstream of the users, and display relevant ads to their target customers. The healthcare industry is using predictive analytics to predict illnesses and forecast potential medical conditions to enable preventive care and diagnosis.

Predictive Analytics – It’s All About Data

Organizations are turning to predictive analytics to predict the future of markets and consumer trends. The market insights gained through forward-looking analysis are based on one simple thing i.e. data. Businesses have access to vast amounts of information through various sources such as point-of-sale terminals, browsing history, financial statements, and revenue records, etc. Predictive data analytics utilizes this untapped pool of information also known as big data to analyze and gain actionable insights on the market landscape, consumer trends, and competitor scenario in the industry. The organizations should leverage advanced analytics solutions such as predictive analytics and big data analytics to predict the future, identify patterns, and build new strategic models instead of dwelling over their past mistakes.

Predictive Data Analytics – What Does the Future Hold?

Predictive data analytics leverages statistical modeling, machine learning, and data mining techniques to analyze the past and present data to predict the future. Businesses that have integrated predictive analytics within their processes and systems gain a competitive advantage over the other players in the market. For example, e-commerce players can leverage predictive data analytics to vary their pricing strategy based on shopping patterns, achieve optimal search outcomes, and undertake promotional and marketing activities by targeting the right customer. Predictive analytics find application in finding the right person for the right job by using past performance data. In the future, three to five years down the line, predictive analytics tools and solutions are anticipated to be more context specific, accessible, and flexible in terms of customization.

To know more about predictive analytics and its impact on your organization

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