Marketing plays a significant role in the success of today’s businesses. It helps businesses bridge the gap between themselves and their customers while supporting the success and profitability of these businesses. However, marketing is changing. It is no longer about hypotheses and past experience but about big data and how it can be used to serve businesses that take advantage of it. The use of big data can be used to gain a granular understanding of competitors, the market, customers, and so much more. Utilizing big data, businesses can realize better returns on investment and have the necessary data to put forth and implement effective strategies and decisions. In this article, we will look at the critical role big data is playing in digital marketing as well as how it is revolutionizing it.
Collecting the Right Data
Businesses and organizations are encouraged to collect as much data as they can. However, collecting too much data is actually detrimental. This is because having a lot of data increasing the amount of time it would take to analyze that data and therefore make use of it, Additionally, having too much data increases the chances of having data that is not useful, again increasing the amount of time it would take to glean to separate useful data and make use of it.
Key performance indicators that indicate past performance can help provide a guide on which type of data a business or organization should be collecting. In this instance, a business would be using historical data and performance to help with their present big data initiatives.
All business owners understand price can be a point of competition between them and their competitors and can give them a distinct advantage. However, the challenge is often how to set the right price to remain competitive and profitable at the same time. Historically, criteria like production cost, demand, competitors costs, and more were used. But the use of big data can open up even more factors that businesses can use to better price their products and services. This can include data from deals that have been completed recently, what customers are purchasing, whether they are using coupons or asking for discounts, performance data, and a lot more.
In the B2B sector, pricing is a bit different from B2C because every purchase and deal is different. In these instances, businesses can use big data to make the right price decisions based on their buyers and the specific circumstances surrounding purchases.
Better Keyword Targeting
Almost every online sale starts with a keyword search. It is therefore easy to understand why not targeting the right words can be detrimental to marketing campaigns. Businesses have to ensure that they can be found online when a customer searches for keywords that relate to their business.
In addition to data analytics tools, businesses can use data provided by different keyword tools to see which keywords would work well for them. They can also use these tools to understand which keywords their competitors are using so they can start using them themselves. Keywords that are researched in such a thorough manner perform a lot better than those included just because businesses think they fit better.
Once a business understands which keywords would work best for their digital marketing campaigns, they can start utilizing them in ads, social media posts, online content, and on other digital platforms where their users are likely to find them. Monitoring and analyzing where and how these keywords are being used as well as the results a business is seeing from using these keywords in this manner is critical for the continued success of the marketing campaign.
Better Customer Understanding and Segmentation
One of the ways data is helping digital marketing experts is by allowing them to know who they are talking to and who they should be targeting in their campaigns. This is highly useful because the old way of blasting out messages and hoping they reach the right people is both costly and ineffective in this modern age.
Marketers need to deploy highly targeted, data-driven marketing campaigns. Using customer segmentation software and tools, businesses can create buyer and customer personas to help them better engage with customers who are a lot more likely to engage with their businesses.
Since this is an essential skill for marketers, most marketing and data analytics degrees place a lot of emphasis on teaching the skills and techniques digital marketers need to deploy customer segmentation tools and strategies to meet the needs of today’s businesses. Marketers can learn how to combine marketing and data analytics skills at Emerson College by enrolling in their Master’s degree program geared towards digital-savvy marketers who want to thrive in today’s market.
Building on the last point, personalization is a key strategy that works hand in hand with customer segmentation. In addition to posting high targeted messages, markets also need to know when the right time is to send the message. Big data can help with this.
Businesses can use data such as geolocation, click behaviors, and purchasing history to know the exact right time to send a message to their customer or a segment of their customers. For example, if a business understands that its customers take a certain type of coffee at 9 AM in summer, they can send personalized promotional messages around that time to encourage customers to get their favorite type of coffee at that time. This type of granular targeting is only possible through both customer segmentation and highly personalized targeting.
Other types of personalized marketing include product recommendations, targeted ads, and targeted social media posts.
Understanding Customer Retention Rates
Digital marketers should aim to have a high customer retention rate; the number of customers returning to the business after an initial purchase or interaction. Measuring and understanding your customer retention rates is all about collecting data on your customers such as which credit cards were purchased more than once or how many return coupons have been used.
Once businesses understand their customer retention rate they can start putting measures in place to retain these rates or increase them if they are too low.
Showing Returns on Investment
Every customer or lead action has some cost. Accordingly, it should have some return on investment, whether that is through an email left by a visitor or a purchase. Big data, data analytics, and visualization can be used in tandem to show both the cost and the return on investment of each action a visitor or customer takes.
This can be done by using tracking techniques to see what is driving the most traffic and sales as well as where money is being spent without any return. This data can then be used to optimize and improve a marketing campaign to better tighten up and improve return on investment.
Using data collected from their customers, businesses can also find out what types of products their customers buy and when. They can also find out which payment methods they use and use all this information to reach out to these customers with the right offer. The right offer presented the right way at the right time has the potential to nudge a customer towards purchasing thereby helping increase sales.
With all the talk about sales and profitability, all these points are moot if a business does not have any products in stock. Poor demand forecasting leads to businesses running out of stock, which can be particularly bad in a season where there is a high demand for a certain type of product. Big data and data analytics help businesses collect data on trends, sales data, demand, and more to help with demand forecasting. In many cases, predictive and prescriptive analytics are also used to make the demand forecast as accurate as possible.
Demand forecasting is also important for manufacturers because it helps them increase and decrease production according to demand forecasts. This helps manufacturers avoid stockouts in periods where there is very high demand and warehousing and storage costs when there is low demand but a high volume of product being produced.
Digital marketing is expensive and so every dollar should be utilized as best as possible. In this digital age, marketers use a lot of different digital mediums such as blogs, social media, emails, and affiliate marketing, and ads to reach their customers. Digital marketers are able to know which of these mediums has a decent return on investment so they can focus on these channels and discard the others.
In determining which channels to put money into and which ones to ditch, digital marketers will look at conversions, revenues, and which channels lead to more purchase and sale opportunities. Doing this helps marketers manage their budgets better.
Big data has necessitated the growth in the demand for marketing and data analysis. Big data and data analysis has become so useful for marketers and businesses that they are unlikely to go away any time soon. This is especially true looking at all the benefits and ways that big data and data analysis are revolutionizing digital marketing.
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