The document discusses the integration of data science into business processes, highlighting its role in predicting customer behavior, optimizing inventory, and enhancing customer engagement. It emphasizes the importance of understanding consumer needs for product development and security, alongside the ability to predict future market trends for strategic advantage. By leveraging data, companies can improve efficiency and customer satisfaction while driving revenue growth.

1. DATA SCIENCE
PROCESS:
RESOLVE BUSINESS
THE SMART WAY

2. What happens when you decide
to incorporate data science
process into your business?

3. The transactional & customer engagement data taken at various points from the
customers such as the feedback on products, services, etc. helps the data scientists to
predict the return on investment for the company.
Also, this data helps the company design products according to the demand pattern of
the customers, hence improving the customer base. The marketing analytics designed
with the use of predictive analysis is further able to attract valuable clients.
Increase in The Number Of Customers

4. The customer demographical data is paired with the product he/she buys and is
recorded for future reference. This type of data helps understand the type of customers
a business must look forward to attracting.
Also, when the customers are presented with other products, their interest in any
particular product is recorded, so that demand can be anticipated. Recommendation
engines can help in up-selling other products to increase business revenue &
recommendations also works as customer delight.
Better Customer Service

5. Apart from improving the sales and customer demands, the company itself needs to
function properly. It necessitates ensuring that all the equipment installed in its facilities
is working efficiently.
The industries that deal with perishable goods need to make sure that they do not have
extra stock in their warehouses. Data Science can help business owners in inventory
optimization. The idea here is to predict the problem before it actually appears so that it
can be avoided by hampering the efficient working of a company.
Improved Efficiency

6. How can data science be used to
solve business problems?

7. Innovation is the key to surviving and sustaining in the business world. But
understanding the pulse of the customers is even more important to know which
upgrades and improvements to the existing products/services will be accepted by them
and which will be pushed aside.
It’s been the biggest secret that organizations are trying to hack every day. Complete
understanding of consumer behavior is nearly impossible, but data science can shed
light on this matter with a great level of accuracy. The right set of improvements done as
per customers’ feedback can make the product/ service widely acceptable in the
market within a short span.
1. Upgrades and Improvements

8. Having an idea is nothing till it gets executed properly. Even if the idea gets executed, it
needs to match the customers’ expectations and should be able to solve their pain
points. A great example would be streaming company Netflix, which started as an
alternative to movie renting but has exponentially grown to become an integral part of
every household. From movies to series to games, it dovetails into the vast pile of data of
customers’ sentiment and behavior and brings the best insights out of it. Every
successful product/service company does the same.
2. New Product or Service Development

9. Those days are long gone where manual security used to suffice the protection
measures. Machine learning algorithms merged with AI can enhance security
parameters to global standards. From fraud detection to data scanning, it can be
leveraged widely in security use cases. Multiple companies are going through the vast
set of data for finding patterns and ensuring no security issue is left unchecked. More the
cases are backed by data, the easier it is for the security personnel to verify, validate
and fix it.
3. Security enhancement

10. Identifying the next market trend can be the pivotal key for bringing a revolution in
business. What customers would need in the future, being able to predict that, is nothing
less than a superpower. Companies that stay ahead of the curve, have always been
leveraging the data to understand and predict the next big thing in their respective
industry. For example, a Nielsen study found out that a whopping 81% of the customers
want companies to take environmental sustainability seriously. Clothing retailer
Patagonia considered that and launched a worn-wear site, which helped their
customers to recycle used products, and in return, brand loyalty improved drastically.
4. Future market trend prediction

11. Read the full article
https://www.datatobiz.com/blog/data-science-process-solve-
business-problem/