There are hundreds of areas in which big data analytics revolutionizes marketing and sales department in the businesses. The analytics shows how prices are predicted, defined, and managed through selling networks and are optimized to see rapid gains. Gaining more price optimization for a given product or service is becoming possible day-by-day, thanking to new advances in big data algorithms and advanced analytics techniques.
The most beneficial aspects of marketing is the ability to form data-driven insights that inform the marketing strategy. There are a number of marketing data and analytics tools available, there shouldn’t be any reason for the marketing team to fail to leverage big data relevant to the business.
Big data, in short, is a large set of analytics and statistics that allow businesses, irrespective of its size, to find patterns and trends relevant to their market.
For instance, the businesses may find patterns in the types of website visitors to attract the targeted audience, trends in the number of clicks certain pages are getting more.
Max Galka, data visualizer, and founder of Metrocosm, says, “The challenge is there’s a ton of data. To use that data in a meaningful way, you need to know how to collect it, analyze it, and display it. A second challenge is the data is spread out in many tools and platforms. This means your team is missing out on untapped opportunities without this complete picture.”
A study asked several Chief Marketing Officers where big data has the largest impact on their respective marketing programs. 58% said SEO, email marketing. 49% said customer segmentation. Around 42% said big data is having the largest impact on the marketing strategy.
Types of Big Data for Marketers
Generally, marketers are interested in different types of big data marketing. There are different sources from which Each type of data is typically obtained and stored in different locations.
This type of data helps to understand the Organization’s target audience. The obvious data type are facts like names, email addresses, inventory, purchase histories, and web searches. The audience’s attitudes or insights can be gathered from social media activity, surveys, and online communities.
Operational type of data is related to the business processes, it is related to customer retention, customer relationship management systems, shipping and logistics, or feedback from other sources. Analysis can lead to improved performance and reduced costs.
Financial data helps to measure performance and operate more efficiently. The organization’s sales and marketing statistics, costs, and margins fall into this category. Financial data such as pricing is also be included in this category.
Uses of Big Data Analytics in Marketing
Big data exists to help better understand and predict the customers and their behaviors. Focusing on how sales and marketing teams can flawlessly work together to increase business within a company, big data can be used in sales and marketing to improve analysis, reporting and results.
It is certainly not up to sales and marketing to determine overall pricing and taking care of finances of products and services. In businesses, there are times throughout the year that big data can help them to offer pricing optimization suggestions.
For instance, the business is trying to clear the place of a particular product in order to make room for a new launch or release. Taking a look at data from previous sales to determine which pricing level generates the most sales can help the business get rid of the old product even faster.
Personalize Customer Experience
Every business moves toward with content marketing and there is a huge increase in content. It has made difficult for users to find the right information for their requirements.
On the contrary, the competition on every digital platform has increased significantly. To compete efficiently businesses need to offer their content to a targeted audience. There are companies like Microsoft, Facebook, and Google use big data analysis to enable advertisers to target content with people of desired interests and behavior. Now, companies can perform such analysis at an individual level.
Analyzing the data about customer behavior and interests, Organizations can create recommendation engines that can deliver content to the consumers which they will likely engage with. Using these techniques brands can not only enhance the online experience but also improve the in-store layout and marketing messages.
Improve Allocation of Budget
To improve the allocation of wealth and resources, it takes planning, measuring, and analyzing to determine possibly the best budget for a marketing team.
Nevertheless, big data can help the marketing team to ensure that it’s allocating the budget in all of the accurate areas. Instead of guessing based on studies of other businesses and their performance on each platform, the sales and marketing teams can take a look at the particular business’s specifics. Then the businesses can allocate the budget across channels based on where the best results are noticed in the past.
Insight of Customer’s Emotions
There is a common mistake in considering that data analysis in marketing will only yield analytical results. But emotional intelligence is an integral part as well, data science is only thought as a complementary tool. With latest advances in technology, human emotions can be understood and analyzed.
With the help of sentiment analysis, companies are able to understand the emotion behind a text. This technique is used to study the communication regarding a brand on social media platforms, blogs and review sites to understand the collective market opinion towards it. The chatbots are also helpful in understanding the consumer emotions as the entire communication history can be recorded.
Knowing the journey can help improve customer relationships, improving customer loyalty and securing the trust. The Data-driven insights can help the sales and marketing teams to understand each specific step customers take before they make a decision to buy.
By analyzing text within emails and posts, technology can read between the lines and help grasp the underlying sentiments.
Highly risky business demands for better risk management processes. A risk management plan is a critical investment for any business of any sector. Able to forecast a potential risk and solving it before it occurs is crucial if the business is to remain profitable.
Big data analytics has contributed greatly to the development of risk management solutions. The data analytics tools allow the businesses to model risks.
Supply Chain Management
Big data offers supplier networks greater accuracy and insights. Through big data analytics suppliers are able to escape the constraints in supply chain faced in the past.
With the modern approaches built on big data, the suppliers can leverage on higher levels of contextual intelligence which is necessary for supply chain process. Modern supply chain systems is to build on high-level collaboration to achieve contextual intelligence.
Know Google Trends to plan the strategy
Google Trends is one of the most approachable method of utilizing big data. It shows trending topics and how often a particular search-term is entered relative to the total search volume. Global marketers use Google Trends to assess the popularity of certain topics across countries or languages they might be interested in, or might be relevant to their buyers.
Implementing big data analytics in marketing team of a business can achieve competitive advantage and reduced cost of operation. As technological advancements continue, data is becoming readily available to all organizations.