Caleb Andrew's blog : Why Data Analytics Is Important in the Automotive Aftermarket
The automotive aftermarket is also growing rapidly to keep
pace with competition, and with the changing requirements of the consumer.
Supply chain disruption, economic insecurity and a shortage of new vehicle
stock have caused consumers to hold onto their older vehicle rather than buy a
new one. to the new consumer of today, “keeping their car running” simply won’t
be good enough. They want that customization and “smart” automation options
with features that are tailored to them and they can customize to make their
driving experience the most efficient. The market needs to respond to
anticipated consumer demand and at the same time pivot to provide new products
centered on trends.
There is a great need to quickly identify and rectify the
pain areas, in this competitive environment. Below are typical issues I see in
this market:
Special industry conditions: The automotive aftermarket is in a category by itself. There is a hunger for lightning-fast turnarounds and manufacturers, suppliers and distributors must be able to keep inventory clean in order to respond to it.
Visibility Woe: Suppliers suffer from visibility across the
supply chain. Without accurate visibility of sales and inventory information in
the market, the result will be OOS problems making it nearly impossible to meet
customers’ time-sensitive requests.
Product turnover: The high pace of inventory turn hinges on
efficient product decision making for production and cancelation to profit
along with the needs of customers.
The rise of data-driven decision-making
The automotive aftermarket is also increasingly adopting
data-driven solutions to counteract some of these challenges. Companies are
using data on customers, products and operations to make smarter decisions,
find new markets and optimize the work force.
Understanding customer behaviour: Delving into customer data
can offer up insights into purchasing behaviour, preferences and the demography
of the customer. This data can be utilized to customize marketing campaigns,
deliver more targeted customers and generate better customer experiences.
Trend spotting: You can try to anticipate demand for
individual vehicle parts with data analytics. Knowing how and when a certain
part is going to be in demand in certain parts of the country allow aftermarket
enterprises to adjust their purchasing and marketing plans in order to reduce
waste and maximize profits.
Inventory management optimization: Based on a study of
historical sales data and demand profiles, businesses can stock the right parts
in the right amounts ensuring that overstocking and understocking do not occur.
This helps to ensure that customers are able to locate the parts they require
at the time they are needed and drives customer satisfaction and reduces waste
related to excess stock.
Enhancing price strategies: Data analytics can also help to
ascertain the right pricing strategies. Aftermarket companies can determine
competitive, yet profitable prices by examining market conditions, competitors’
prices and customers’ actions. It is also possible to use dynamic pricing
models with which prices can adapt in real time with changes in demand and
supply.
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