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How Actionable Analytics Has Transformed The Retail World Through Machine Learning


Businesses are experiencing phenomenal growth by harnessing the power of IoT retail analytics to optimize business operations and enhance customer experience. – PowerPoint PPT presentation

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Title: How Actionable Analytics Has Transformed The Retail World Through Machine Learning

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Time has witnessed how demands of people to have
a luxurious and comfortable life are continuously
increasing. With a smart phone always in their
hand, people are looking up to make themselves
familiar with the new emerging trends so as to
keep up with the rapid pace of change in the
world. Therefore, to meet the demands of people
and have a competitive advantage, retailers make
sure to deliver a great customer experience to
increase sales. This is where retail analytics
plays a huge role for retailers. Retail
analytics provides deep insights to the retailers
about consumer demand, sales, customer behavior
etc. It helps retailers to know about the
strengths and weaknesses of their store and the
key areas of improvement for business
growth. According to Mordor Intelligence, The
worldwide retail analytics market was valued at
USD 3.78 billion in 2017, and is estimated to
reach USD 10.34 billion by 2023, registering a
CAGR of 18.26 over the forecast period of
Below are the 5 reasons why retail analytics is
important for business growth

1. Enhance Customer Experience
Retailers make strategic decisions to enhance
customer experience on the grounds of data
provided by retail analytics. Store managers can
track employee activity and ensure if their
employees adhere to the mandatory SOPs in dealing
with the customers or not. Footfall data helps
retailers in determining the peak hours of store.
Hence, by monitoring footfall, retailers mobilize
the store staff accordingly so as to reduce the
waiting time of customers and enhance customer
experience. Unkempt aisles look confusing and
they greatly hamper the shopping experience of
customers. But retail analytics helps retailers
to optimize product placement and enhance store
2. Insights Into Customer Behavior
Understanding buying behavior of customers is
very crucial for business growth. Retail
analytics helps retailers get insights into
customer behavior by mapping their journey from
the minute they enter the store to the moment
they leave. It aids retailers in optimizing
product placement according to the needs of their
customers. Shoppers Stop leveraged big data
analytics to study buying patterns of its
customers. Based on the findings and insights,
the retailer created targeted promotions for
trousers, which resulted in an additional sales
revenue of 10 crores in a span of three weeks.
3. Optimizing Business Operations
Actionable analytics for retail aids store
managers in optimizing business operations and
boost sales. Through machine learning, retail
analytics studies sales data and provides useful
information to retailers about the brands that
are more popular and the products that are star
performers so that the best-selling products of
the store do not go out of stock. Retail
analytics identifies and reports gaps in employee
productivity and helps retailers to optimize
operational efficiency by terminating unwanted
processes. SOP compliance is another factor that
impacts business operations of a retail store.
With retail analytics, store managers can easily
track employee activity and ensure if they work
according to the predefined SOPs or not.
4. Roster Management
Retail analytics helps discover peak hours of
the store. This data aids retailers to schedule
the shifts of the store-staff accordingly by
preparing rosters on a weekly/monthly basis.
Retailers manage work schedules according to
store traffic rather than employee availability.
Therefore, retail analytics helps in OPEX
reduction. Cycle Gear, an American retailer of
motorcycle parts and apparel, is using data to
drive business strategy and increase sales. After
just 5 months of deploying people counting
solution, the specialty retailer experienced
their best Black Friday sales and increased
quarter-over-quarter comp sales, across 140 store
locations in 38 states, while keeping its wage
budgets in line.
5. Revenue Enhancement
Big data churned out by retail analytics,
reports about the performance of retail store to
the stakeholders. On the grounds of this data,
retailers make informed decisions to fill the
gaps in business processes and increase
conversion rate. Starbucks, uses big data
analytics to predict the growth potential of each
new store by looking at metrics such as location,
traffic, area demographics and customer
behaviour. Starbucks collected insights from
their 90-plus million transactions per week and
used this data to deliver a personalized
experience to its customers. Big data helped
Starbucks in maximizing profits. Therefore, it
reported revenue of 22.39 billion in
2017. According to IBM, 62 of retailers report
that the use of big data is giving them a serious
competitive gain.Click to tweet Consequently,
Retail analytics solution that leverages
artificial intelligence and evolves through
machine learning algorithms has helped retailers
gain competitive advantage by increasing customer
retention and driving great profitability.
KocharTech is one of the largest enablers of the
connected device ecosystem offering comprehensive
solutions to a number of retail clients to
enhance their business growth. We focus on the
business benefits that technology can bring and
help brands deliver the best customer
experience. Our experience in retail ranges from
optimizing business operations, providing
insights into customer behavior and drive
profitability in business. To augment business
growth from technology, Get in touch with us.
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