Predictive Analytics for Startups: Opportunities Abound

While success doesn’t come easy for most start ups (unless of course you have played all the right cards); most startups see a dead end within a few months of starting. 

In many cases, the reasons for this early shut down are – ambiguity of goals and objectives, inability to implement the ideas effectively, creating the right market and finding the right customers, and of course lack of funds.

 How, then can start-up entrepreneurs avoid running into such a situation? 

Technology, in particular, “Predictive Analytics” is the answer says Martin Zwilling, founder and CEO of Startup Professionals. He says, “Predictive analytics uses data patterns to make forward-looking predictions that guide you to where you should go next. This is a whole new world for start-ups seeking enterprise application opportunities, as well as social media trend challenges”.

It is imperative for startups to be particularly be sure of their next several steps after inception; Predictive Analytics fits the bill perfectly here by keeping startups educated and informed about these business aspects – how their market is going to behave over the coming months, who would want their products and services the most and why, what are their competitors up to; what should they be prepared for.

       Zwilling lists the following “creative ways” in which startups can leverage Predictive Analytics: 

            Identify and target customers correctly:

Use Predictive Analytics to consolidate what Zwilling calls a single view of the customer; based on which you can improve your promotional and marketing strategies aiming the right product to the right customer with the right needs.

Manage your investment risks:

As a startup, you will be often skeptical and apprehensive while making new investments for your startup’s growth. Predictive Analytics minimizes those risks by giving you accurate details of how your choices are currently positioned now and how are likely to do in future, thereby helping you decide if your investment choices are worthy or not.

            Customer retention: 

I have spoken about this at length here. And Zwilling only strengthens my opinion that Predictive Analytics helps organizations, especially start ups to identify and resolve the causes for customer attrition. 

            Fraud detection: 

Startups in the BFSI sector can use Predictive Analytics to identify faulty transactions, fraudulent customers, improve underwriting, assess a customer’s financial profile, minimize false insurance claims and even bust false identities.

To know how Shout Analytics’ Predictive Analysis capabilities can benefit your business, either startup or established, write to us at info@shoutanalytics.com

 

Top 30 Uses of Predictive Analytics

Predictive Analytics will be the force to reckon in the future because of its power to predict and foretell industry events based on the previously existing conditions. In other words, predictive analytics helps organisations across industries to anticipate negative events and misgivings thereby helping them to prevent failures and frauds.

While most Analytics gurus opine that Predictive Analytics is best suited for financial institutions, we believe that it is equally beneficial to any organisation that wants to be prepared for the challenges and opportunities of the future.

Therefore, we listed 30 uses of Predictive Analytics for various organisations:

Banks:

• Improve customer service
• Build and nurture great customer relations
• Detect and prevent fraud
• Sharpen your businessintelligence
• Plan future strategies and chart out revenue boosting methodologies

Financial Services:

• Anticipate risk, especially interest rate risks and price risks
• Calculate credit scores with greater integrity
• Increase accuracy while making pricing decisions
• Prevent future risks and reduce defaults
• Curb fraud – be it in transactions, customer authenticity or credit applications
• Credit card companies – take charge of credit lines
• Zero-in on the right customer to sell your new offers

Insurance:

• Enhance underwriting by leaps and bounds
• Be well informed of the risk factors while fixing premiums
• Alleviate fraud –  false claims and wrong claimant profiling

Retail:

• Forecast sales, improve service and buying experience
• Understand customer purchase behavior
• Target the right product for the right customer
• Accentuate product marketing and promotions
• Improve store(s) management
• Streamline and take control of overall operations 

Government

• Better decision making – back important policies and bills with concrete data
• Predict electoral results
• Detect fraud
• Study citizens’ reaction to government policies and measures
• Predictive Analytics was used extensively in the US during the 2012 presidential election to find newer ways to persuade voters.

Sales and Marketing

• Know whom to target and with what products
• Increase sales; save time
• Propel cross selling
• Boost customer service, customer relation management and customer retention

So, if you belong to any of the above industries, you have reasons enough to invest in Predictive Analytics. Do you see/ look forward to any other uses of it? Share your thoughts in the comments below or write to us at info@shoutanalytics.com.

The Power of Predictive Analytics in Helping Banks Build Excellent Customer Relationship

Wouldn’t it be great if banks could foretell which of their customers would be a perfect potential buyer for their latest credit card or home loan? Well, Predictive Analytics can help banks do exactly this and much more.

Banks deal with voluminous streams of unstructured big data. Using cutting edge social media analysis tools and Predictive Analytics tools in particular, banks can closely monitor their customers’ banking behavior; depending on which they can pitch new offers and promotions with greater success. 

A banks’ marketing department is often faced with intriguing questions like these –

•   Which customers would opt for what promotions
•   Would combining offers on loans and credit cards be a hit  ?
•   Which offers and promotions would attract new customers

Similarly, the bank’s operations manager would want answers to questions relating to detecting and identifying fraudulent customers, credit card faults, and account mismanagement. He would also want to identify and reward the banks’ long standing, loyal and ‘bank-perfect’ customers.

Predictive Analytics helps banks find answers to the above questions. From the time a new customer makes his first transaction till he turns into an influential brand advocate for the brand, banks can use Predictive Analytics to make him a happy customer and build a healthy relationship with him. 

To start with, banks can pinpoint exactly what services and products the new customer prefers the most by identifying his banking behavior pattern. This also indicates his responses to new offers and products, thereby telling the bank if he is the right prospect for the new product or not. Over a period of time, as the new customer becomes a known customer; predictive analytics can help the bank to craft tailor made services to him. 

Thus, aided by predictive analytics, when banks make sustained efforts to know, understand and provide need-centric services to their customers, they succeed in nurturing and growing a group of loyal customers who only have good things to say about their bank. These customers (remember, you and predictive analytics made them that way) are strong brand advocates who are powerful enough to influence others (read potential customers) banking decisions.

How else do you think Predictive Analytics can benefit banks? Share your thoughts in the comments below. To know more about Shout Analytics and its Predictive Analytics capabilities, write to us at info@shoutanalytics.com

Social Media for Artists and Fans, Social Media Analytics for Films and Production Houses

Friday is just round the corner and that means a slew of films are slated for release. As film buffs around the world get ready to savour the performances of their favourite actors and works of their favourite directors, they, do not realise how important a role they are playing in this age of social media analytics.

As social media gets accepted and endorsed as a vital technological assistance in film distribution and marketing, entertainment houses are slowly discovering the Predictive Analysis capabilities of social media analytics tools with regard to opening day sales and box-office performance based on the sentiments and vibe surrounding their film on the social channels.

While social channels allows actors, producers, script-writers, lyricists to connect and engage with their loyal fan base, it also helps fans turn into critics and reviewers by allowing them to give their instantaneous verdict for every film they watch through real-time tweets and Face book posts. Review forums, discussion boards and YouTube comments are also other social spaces that movie goers use excessively to tell the world how much they liked or disliked a movie, its actors, storyline, music, dialogues and everything else. 

So you see, in the wake of such heightened usage of social media by the consumers of films and motion pictures, it becomes imperative even for production houses to rely on social media analytics in order to explore, understand and extract the right piece of useful information from tons of social media data and further use that useful information to make the right business impacting decisions. 

Advanced and big data competent social media analytic tool like Shout Analytics helps entertainment houses to predict trends, activities and behaviors using cutting edge predictive analysis and sentiment analysis techniques. Shout Analytics makes possible precise social media monitoring and management, gathers actionable insights from the film and entertainment industry to equip you with critical business intelligence to reduce financial risks, discover newer avenues for investment and multiply profits across production, distribution, promotion and marketing.  

If you are a motion picture company or a production house and are looking for social media Analytics solutions for your organization, then write in to us at info@shoutanalytics.com

5 Reasons Why Banks Must Use Predictive Analysis

Beth Schultz, in her blog post on Predictive Analytics revealed an interesting story about how her friend was offered refinancing of her mortgage by her bank, Chase Bank. This was the bank’s reward to her for being a long standing loyal customer. 

How could Chase Bank probably have arrived at such a decision? The answer lies in Predictive Analysis. 

 

Today, as banks and financial institutions realize how imperative advanced real-time analytical solutions are for running their organizations, they are also looking for constructive predictive analysis tools. 

Here are some of the uses of predictive analysis for banks:

Right Product for the Right Customer:

Using predictive analysis tools, banks and financial institutions can track individual customers for specific buying habits and derive a distinctive pattern, using which they can easily categorize the customers on different parameters and offer them services and products specific to their needs and wants.

For example: consider that one of your customers is an NRI, whose account, over a period of time has seen a lot of transactions for buying or selling of property, indicating that he is investing heavily in real estate. Perhaps then, wouldn’t a tailor made home loan with special benefits to NRIs be just the right product for him? This is also an effective way to decrease customer attrition.

Manage and Maintain Brand Reputation:

Are your twitter streams bombarded with tweets from dissatisfied customers or is your Facebook wall filled with negative comments and complaints about your products and services? Well, left untreated, this negative sentiment could take on giant propositions and do grave damage to your brand reputation.

Using predictive analysis, banks can assess the reason for increased negative sentiments about their brands, fix the issue and thus prevent these instances from snowballing into a PR crisis.

Detect Fraud:

Are some of your customers always finding their way to the defaulters list? Repeatedly? May be they are not legitimate customers at all. With Predictive analysis, you can easily find out.

Better Customer Insights:

Banks and financial institutions nurture a huge repository of customer information both personal and financial. But the key lies in using this information effectively to increase revenue.

For example: using predictive analysis, if an IT manager took a home loan and a car loan together but has now been defaulting every now and then on both EMIs, then may be it is an early indicator that he could have difficulty repaying both the loans. 

Thus, predictive analysis tools are extremely beneficial to banks with regard to improving customer relations, increasing revenue and strategizing their marketing initiatives.

Shout Analytics provides cutting-edge predictive analysis services to BFSIs. So, if you are convinced that your organization needs predictive analysis tools, contact us at info@shoutnalytics.com