Business analytics solutions the pulse of intelligent retailing

Business Analytics Solutions, The Pulse of Intelligent Retailing!!

Customer expectations & experiences offered to users across the channels remain on the top of the priority list for Retailers across the globe. When strategized methodically with the help of combination of contemporary technologies like Business Intelligence services & Analytics, IoT, sensor based solutions like the Beacons, Social Media, Apps, the Cloud and more, Retailers have no looking back.

An Insight into Our Thoughts For Retail

Retail Analytics with the Tiny Beacons & Big Data – Contrasting but Complementing The Disruptive Retail Apps! Heralding an Innovative Age for Buyers & Sellers!!

Personalize your Retail Apps Solutions and Keep your Clients Coming Back for More The Big Rise of Smart Retail with the Tiny Beacons Cool & Cooler- The Millennials; A Disruption to Retail Shopping Experiences

Data Analytics Becomes Inevitable for Retail Sustainable lifecycles of retail processes for all major players globally, integrate business intelligence & data analytics effectively into the processes. This includes sales forecasting, demand projection with predictive simulation, customer heat-mapping, product placement optimization as well as keeping a tab on the emerging products topping the popularity charts.

Analytics & Business Intelligence sense, comprehend & provide insights incognito & efficiently

By analyzing past purchase trends, data analytics drills to find an appropriate technique to identify customers that would be interested in a certain product segment, tackle them with specific marketing strategies and eventually determine what will be the next saleable commodity.

Putting Data Analytics to Use for Retailers As data analytics integrates seamlessly into Retail, making the most of this niche to the advantage of the enterprise becomes the done thing.

Predicting Demand Intelligently Retailers can focus better on areas that are more in demand the instant they get the real picture of consumers buying trends. Demand prediction includes collecting demographical, seasonal and occasion specific data along with economic indicators that help chart a behavioral picture of purchase trends spanning the target market.

Inventory management gets a boost with this practice too without a shortage of any critical item at any given time.

Predicting the Future Every customer interaction curated & interpreted by business analytics solutions have a definite impact on current as well as potential relationships in the retail sector, making future performance prediction an important aspect.

Using a test-and-learn approach has been identified as the best technique to keep a check on cause-and-effect relationship among strategic shift & key performance indicators by top enterprises globally, especially in Retail‌.

This process is governed by analytics conducting performance comparison continuously.

Trend Forecasting To get a better know-how of current patterns, retailers have a choice of advanced tools & techniques based on analytics to depend on. The discreetly captured big data serves as an input to BI algorithms that are involved in trend forecasting. Such algorithms analyze the promotional needs by marketing departments, and also help make decisions regarding the fronts where promotions are not required.

Optimized Pricing Price determination is area where data analytics plays a key role by varying prices in accordance to the demands forecasted using principles of Marketdown optimization focused on appropriate determination of the timeframe when prices are to be reduced.

Before the methodical approaches of Analytics came into practice, retailers simply lowered prices during off-season when the demand for a particular product was nonexistent or minimal. However, analytics has proved that opting for a gradual price drop when demand starts to reduce eventually helps maximize revenue for a particular product or commodity.

Today, retail giants, like Walmart spend millions on perfecting their real time merchandising systems with the view to setup the largest private cloud globally..

The objective is to keep a close eye and track the daily happening transactions, whose volume is in millions. Sophisticated algorithms perform this function along with other tasks‌

Customer Identification Business intelligence services proves to be a dependable method when it comes to identifying which customers would be interested in a particular product. This has resulted in a wide variety of retailers relying on online recommendation engines, offline as well as online data compiled by loyalty programs and transactional records.

Personalization for Engaging Better Personalization is the magic mantra for the millennial age and Analytics remains at the core of this approach. Most important aspect for retailers, personalization drives the retail businesses today.

Identifying highest Return on Investment (ROI) opportunities After retailers have a real-time picture of their current and potential customer base, they make the most out of predictive risk filters & data-driven intelligence helping the Retail industry strategize the marketing approaches.

Diving in Deeper with Analytics And there is more than what meets the eye.

Reducing the Churn Rate Today, the cost of engaging a new customer in retail business is probably six times more expensive than retaining an existing customer, which makes the customer loyalty a top priority for all.

The churn rate can be represented in different formats like percentage of recurring value lost, overall value of recurring business lost or percentage of customers lost.

Data analytics enables businesses to gain insights into details such as which customers are likely to churn, which eventually allows retailers to alter their offerings or subscriptions to control such situations.

Improving Sell-Through Rate Retailers can easily analyze products that have a strong correlation to data. This is done to determine the kind of visuals, jargon and pricing that synergize with current as well as potential customer base. Retailers avail improved sales ratio based on the product showcase related to the analyzed data sets.

Uber Putting Analytics to Use

Maintaining Efficiency of Discounts Surveys have indicated that 95% or more shoppers tend to avail coupon codes while shopping. Retailers need to carefully analyze the deal value for their prospective business to benefit from such offers. Promotional deals may attract customers in a rush but may not be favorable to retain customer loyalty in the longer run.

A better option for retailers would be keep long term strategy at the forefront, and then analyze historical data to come up with predictive modeling, that gauges the impact of such offers. As an example, a cohesive team of scientists & data analysts can closely examine historical events that might have resulted in absence of discount or related offers.

Moving Ahead Business analytics solutions indeed capture the interest of major players in the retail sector. To keep abreast with competition in areas like brand promotion, score improvement when it comes to promoters and customer loyalty, a major chunk of retailers use solutions offered by BI & Analytics across channels to positively influence sales.

Analytics also becomes an affordable & indispensable offering for the smaller retailers too who leverage this approach on various channels to tap the nerve of the market and personalize efforts to engage the customers.

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