Omnichannel Analytics
Transform from Transactions to Relationships
Omnichannel Analytics
Transform from Transactions to Relationships
To win the loyalty of millennials, you have to understand them and their lifestyles, listen to them, understand them and serve them the right product at the right price and place. Multiplication of retail channels and increasing use of mobile technologies are empowering consumers with a wealth of information at their finger-tips. Even as they shop in stores they can easily browse and compare products, services and prices online.
Thus retailers need ways to collect, store and analyze the volume, variety and velocity of data which is not possible by traditional technologies. By addressing the challenges of Big Data you can generate insights to personalize marketing campaigns, optimize assortment and merchandising, remove inefficiencies in supply-chain and overall capitalize on the new business opportunities that omnichannel world presents.
To win the loyalty of millennials, you have to understand them and their lifestyles, listen to them, understand them and serve them the right product at the right price and place. Multiplication of retail channels and increasing use of mobile technologies are empowering consumers with a wealth of information at their finger-tips. Even as they shop in stores they can easily browse and compare products, services and prices online.
Thus retailers need ways to collect, store and analyze the volume, variety and velocity of data which is not possible by traditional technologies. By addressing the challenges of Big Data you can generate insights to personalize marketing campaigns, optimize assortment and merchandising, remove inefficiencies in supply-chain and overall capitalize on the new business opportunities that omnichannel world presents.
How Big Data can help Retailers Capitalize on Omnichannel Opportunities

How Big Data can help Retailers Capitalize on Omnichannel Opportunities

1

In-store order fulfillment
How do you compete with Amazon’s ever expanding fulfillment centers and push towards same-day or next-day delivery with limited warehouse infrastructure? What if you could analyze data from POS systems, online transactions, social media, loyalty programs and call center records in a single system to deepen your understanding about customer preferences, location and inventory?
In-store shopping experience
While most retailers are scared of showrooming as a phenomena, you can turn it into a benefit. While shoppers are comparing your in-store prices online with competitors you can enable online and app-based brand and product touch points to push personalized content. You can use advanced analytics to gain insight from in-store activities and online behavior to better understand customers.

2

3

Personalized e-commerce shopping
Retailers can personalize their shoppers ecommerce journey by offering personalized promotions and messages. Using a combination of artificial intelligence and advanced analytics you can identify most frequent drop-off points for customers, reasons for such drop off, impact of assisted shopping at various points, thus ensuring higher conversion rates. You can also personalize recommendations by identifying items that are most frequently bought together.
Retail merchandizing
Better understanding of customer buying preferences (both online and in-store), demand trends, seasonal variations, impact of promotions and competitive pricing helps in initiating sales, building customer loyalty and avoiding losing business. With the use of Big Data and analytics, retailers can build customer loyalty programs, optimize merchandizing across multi-channel retail and smarter supply chain and operations.

4

In-store order fulfillment
How do you compete with Amazon’s ever expanding fulfillment centers and push towards same-day or next-day delivery with limited warehouse infrastructure? What if you could analyze data from POS systems, online transactions, social media, loyalty programs and call center records in a single system to deepen your understanding about customer preferences, location and inventory?
In-store shopping experience
While most retailers are scared of showrooming as a phenomena, you can turn it into a benefit. While shoppers are comparing your in-store prices online with competitors you can enable online and app-based brand and product touch points to push personalized content. You can use advanced analytics to gain insight from in-store activities and online behavior to better understand customers.
Personalized e-commerce shopping
Retailers can personalize their shoppers ecommerce journey by offering personalized promotions and messages. Using a combination of artificial intelligence and advanced analytics you can identify most frequent drop-off points for customers, reasons for such drop off, impact of assisted shopping at various points, thus ensuring higher conversion rates. You can also personalize recommendations by identifying items that are most frequently bought together.
Retail merchandizing
Better understanding of customer buying preferences (both online and in-store), demand trends, seasonal variations, impact of promotions and competitive pricing helps in initiating sales, building customer loyalty and avoiding losing business. With the use of Big Data and analytics, retailers can build customer loyalty programs, optimize merchandizing across multi-channel retail and smarter supply chain and operations.