I am a big fan of walking into a retail store versus buying things
online. This is specifically true for clothes from my favorite retail
chain since it gives me access to physically see a wide variety of
options combined with great ambiance, music, and sales assistants who go
the extra mile to help me make the right choice. I fear I end up buying
more items than I planned, but the store-buying experience makes me
feel valued as a customer. However, before I head to the store, I check
out the store’s website to see what’s new, find different colors and
styles, and sometimes add things I like to the online cart.
I am
also a huge admirer of social media. I often use Twitter as a way to
communicate with my retailer and check out their Facebook page to see
what’s new. When I am in the shop, I check-in to the store using Swarm
(Foursquare). When you look from the retailer’s point of view, I am
giving them several ways in which they can communicate with and
understand me. By connecting my interactions via these different
channels with my location data and my preferences, the retailer has a
great opportunity to give me a consistent and quality experience,
leading to a win-win situation for both me and the retailer.
So,
what is stopping these organizations from achieving great customer
service? It is a no-brainer that if they make their customers happy,
they not only beat the competition, but they also achieve their business
goals and become more profitable.
In reality, there are many road
blocks to their success. The trouble with insight is it doesn’t just
pop out of data. It takes intelligence and an understanding of the
business, combined with the ability to identify useful relationships
between customers, their relationships, locations, products and social
interactions. Once you are able to connect these dots, you need a
comprehensive understanding of the content, context and correlations
within. The most important aspect of this exercise is the foundation of
quality data about your customers and products.
This is why Master Data Management (MDM)
has become such a crucial layer in the enterprise analytics stack; it
prepares your customer, product and other master data. MDM identifies
critical relationships among the data and combines interactional and
transactional data associated with your customers. As a result of this
great technology, organizations are now becoming more customer and
decision ready.
As companies are trying to master digital
transformation fueled by social, mobile, cloud and big data, they are
finding it hard to connect data flowing to their organization in huge
volumes and varying formats. It’s becoming extremely difficult for these
organizations to put data to work to identify different relationships
that exist between their customers, prospects, their households, the
products they have bought, the products they wish to buy and locations
they are in, etc.
In last few years, we have seen the advent of
emerging technologies developed to tackle big data. Hadoop, which
quickly gained popularity, has dramatically lowered the threshold of
viability for big data analytics. Designed to run natively on Hadoop, Informatica Big Data Relationship Management
helps organizations handle master data in large scale. It identifies
customers, their household and social relationships that exist across
billions of records representing millions of people. Combining this
information with customer interactions, transaction data and social
media data helps organizations create a “Social 360” view that helps
them understand their customers more intimately.
And,
understanding customers is key to every organization’s success today.
What’s even better for companies is to have the ability to anticipate
what their customers’ needs and wants are and deliver the right offers
at the right time so they can not only meet, but exceed customer
expectations and win them for life. So, the next time I walk into my
favorite retail store, it would be wonderful if they could walk me
straight to the changing room based on what I put in my online cart.
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