Digilytics RevUP: An excellent solution to help auto aftermarket players exceed their sales goals

Although sales leaders in the auto aftermarket segment enjoy tremendous revenue opportunities, from retention to replacement parts, they also have a massive amount of customer data to deal with. This makes it challenging to achieve and exceed sales goals and identify market share and new business opportunities in the sector.

This is where AI and Machine Learning solutions come in as elegant and cost-effective solutions for businesses.

In this post, we explore the challenges faced by auto aftermarket players, the role of data extraction and classification, and how Digilytics RevUP-an an AI-based SaaS product- can be instrumental in exceeding sales goals in the auto aftermarket industry.

Role Of Data Extraction and Classification

The last few years have seen an enormous general interest in the automotive sector, with huge sets of informative data openly available to the public.

Companies involved in the auto aftermarket sector specifically have access to other data sets, including customer preferences of vehicle model, manufacturer and fuel type, and all other details of customer buying habits such as engine size, colour, transmission type, and more.

However, not all automotive aftermarket companies store their data for posterity. While others may make efforts to collect data periodically, they are yet to discover the value and various financial benefits within the data that technologies such as AI, statistical analysis, big data analytics, and data science can offer.

So, how data extraction and data classification can help the auto aftermarket industry? Read on to know more.

1. Addressing Deficiencies Through Data-Driven Decision Making

The power of digital solutions such as AI in auto aftermarket companies develops traceability through the entire supply chain for much better operational control.

Further, the data accumulated tracing, extraction and classification at several touchpoints help companies understand how to effectively respond to various scenarios regarding cost, resource planning, inventory management, etc.

The insights also help the automotive aftermarket company identify and address various operational gaps and improve their service deliveries, strengthening their edge in the market.

2. Improved Resilience in Operations

Today businesses are increasingly opting for a range of digital tools to help them with telematics and connectivity. When it comes to auto aftermarket service providers specifically, these digital tools and technologies can be instrumental in enabling them to strengthen their operations and align their resources accordingly.

This allows their operations to become more robust and resilient. As a result, the auto aftermarket service providers are much more confident when it comes to tackling sudden market disruptions.

3. Unlocking Market Trends

The auto aftermarket is a competitive industry that undergoes fast-changing trends. And one of the excellent ways to keep up with the changing market trends is to use data extraction and classification.

The collection of data regularly can help you spot trends and analyze them and find specific patterns leading to specific events. Making predictions of trends based on data analysis is also a part of predictive analysis and helps you uncover questions such as when do the sales boom? what makes the prices alter? when the competitors come up with new products/deals and so on.

4. New And Better Design Ideas

Data extraction and classification also help automotive aftermarket companies come up with their new and better vehicle design ideas. As you scrape customer preferences and reviews, you get a much better idea of what are customers’ requirements and wishes are, to help you guide your vehicle designing process.

Since every part of the vehicle can be improved as per customers’ wants and preferences, data extraction can be very useful to get information from sources such as customer sentiment data and vehicle sensor data.

Apart from these, predictive modelling is another most important sub-field of data extraction and data classification. It is essentially a combination of AI, machine learning, statistics, and pattern recognition, and its key objective is to predict future probabilities and trends. This kind of data churning can help automotive aftermarket businesses to a completely new level by empowering them with the wealth of knowledge that can systematically guide them through the path to enhanced sales and business success.

How Is RevUP Making the Difference?

RevUP is a revenue growth management product by Digilytics AI, a tech-based organization that intelligently leverages the power of AI and ML to design and develop easy-to-use SaaS AI products.

RevUP uses and implements AI specifically into the automotive aftermarket industry and acts as a single-stop solution to tackle various issues that hinder the growth of revenues. As a revolutionary product for auto aftermarket companies, RevUP offers detailed understanding and allows you to analyze every minute thing. Comprising of three different modules (as listed below), RevUP systematically help you elevate your sales and revenue-

The key benefit of RevUP is that it is a simple plug-and-play bolt-on product that you can integrate into your business without having to make any changes to your existing systems. Offering a safe and secure way to scale your business, RevUP allows you to gain a better understanding of different factors involved in the auto aftermarket along with giving actionable insights to improve overall auto aftermarket business and significantly enhance business revenues.

To Wrap Up

Auto aftermarket businesses constantly aim to make a shift towards a proactive or predictive model, to be able to effectively address the customers' needs, increase productivity and eventually enhance sales.

With Digilytics RevUP, you can not only analyze every data point to gain valuable insight on current performance to drive action that improves both customer and product specific-pricing but also get an advantage in price optimization, market data management, list price management, incentive management, dynamic pricing and much more.