In this data-driven world, the impact of advanced analytics cannot be overstated. Meaningful insights derived from post-analytics can be leveraged to make data-driven decisions of considerable magnitude.
In fact, the big data analytics market, projected to be valuated north of USD 68 billion by 2025, is currently growing at a CAGR of 30%.
With many companies now convinced to overhaul their data architecture and replace legacy systems, big data is paving the way for the efficient management of colossal amounts of data.
“Information is the oil of the 21st century, and analytics is the combustion engine.”
– Peter Sondergaard, Senior Vice President, Gartner.
Hence, advanced analytics is the talk of the town. This article looks at the impact advanced analytics has on a business in 2022. Read on to know more!
How does advanced analytics affect businesses?
With poor data quality costing around USD 3.1 trillion to the US per year, accurate data and airtight advanced analytics systems must be implemented.
But how deep does advanced analytics run its roots into the efficient functioning of your company? How has the impact of advanced analytics been on businesses in the current technological landscape? Read on to find out!
1. Optimize Operations Process
With north of 2.5 quintillion bytes of data being generated on a daily basis, it is evident that businesses have to deal with colossal amounts of data per minute.
All this data goes to waste if there are no proper analytics systems in place to structure it and derive insights.
A robust advanced analytics system can scan the entire system and identify potential loopholes and shortcomings. Once these faults are pinpointed and fixed, the system can proceed to work at a much higher efficiency.
But it would be best if you made sure that the data you feed these systems have to be real-time and accurate to the current industrial landscape. In order to ensure that, leverage reliable data validation services to vet your data repository and rid it of inaccuracies.
2. Obtain In-depth Customer Insights
One of the most profound impacts of advanced analytics is that it helps businesses gain deep and meaningful insights into the customer journey. If you are a successful businessman, you know the answer to this question.
What drives maximum engagement amidst potential customers?
Targeted marketing armed with curated content directly addressing the need of your prospects is what will draw them in.
This is precisely how advanced analytics can make things easier for you. By providing you timely insights into the decision-making process of your target customer segment, advanced analytics clears a path for higher ROI.
Moreover, to gain deeper insight into customer behavior, you can leverage AI and ML to train a predictive analytics model. By using old user data, these models will try and predict the future behavior of a target persona and market trends.
Last but not least, ensure data accuracy by employing efficient data appending services.
3. Enable Faster Decision Making
Without robust advanced analytics systems in place, the critical decision-making process of businesses takes a hit. Moreover, a recent survey also mentioned that 43% of businesses fail to segment data necessary to make essential business decisions.
Employ data verification services and vet your data to obtain accurate industry insights through advanced analytics. The tools leveraged in the process grant you a birds-eye view of structured and segmented customer data.
Moreover, you don’t even need to get into the complicated technicalities behind data analytics. The accurate results and industry insights obtained from accurate data analysis can drive swift and precise decision-making.
4. Helps Decipher Customer Journey
Analyzing the buyer journey of a customer is of the essence when it comes to an understanding your audience. With the customers of the ongoing era being technologically able, they interact with brands via multiple touchpoints.
Operating both online and offline, these customers behave differently in every interaction. For instance, customers sometimes abandon loaded shopping carts because they face an impediment in their purchase process.
By leveraging data from instances like this, businesses can get a deeper insight into the buyer journey and fix any shortcomings that enforce the cart abandonment.
One of the most significant impacts of advanced analytics is that it enables sales and marketing teams to keep an eye on customer behavior. With easy access to in-depth customer journey insights, businesses can tweak their websites and e-commerce platforms to eliminate the existing woes.
5. Sales Process Automation
Advanced analytics can also make way for sales process automation. The primary pieces of the technology behind sales process automation happen to be Artificial Intelligence (AI) and Machine Learning (ML).
These pieces of technology are used to power systems capable of automating many sales processes, given there is a supply of accurate and decay-free data. AI will leverage data from advanced analytics to create meaningful and engaging customer interactions.
For instance, let’s take a look at dynamic pricing. Here, AI is given the ability to trigger a surge or fall in price based on customer engagement. If engagement is high, the price will see an upward trend, whereas the prices will lower if engagement takes a dip.
Moreover, predictive analytics be leveraged to push suggestions to customers based on their previous buying patterns.
Now that you understand the impact of advanced analytics on your business, it is vital to know one more thing. Robust advanced analytics systems are only as good as the data they are provided with.
Hence, always take aid from data verification services and get your data vetted by industry professionals. Once an accurate stream of data is secured, advanced analytics holds the ability to change the roadmap of your organization.
With precise and on-time industry insights, advanced analytics can make way for significantly higher customer engagement and Return on Investment.
Outline your data analytics goals and work towards that objective for obtaining the most out of your big data.