Top Trends in Marketing Analytics

Marketing analytics is the collection of statistical, mathematical, and predictive data about consumers’ actions and behaviors. The goal is to identify the behaviors and attitudes of consumers in order to help businesses make better decisions about how to market their products. Powered by advances in artificial intelligence, machine learning, and statistical modeling, marketing analytics delivers more bottom-line impact with each passing year. 

Marketers need to keep up to date with the latest marketing analytics trends to ensure their marketing strategies are delivering the best results. In this article, we will review some of the key marketing analytics trends to look out for.

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Companies have always used data to try to understand their customers and the market they are in. But nowadays - thanks to advances in technology and data analytics tools -  the use of data has increased massively. And one of the areas where it's used the most is marketing, helping businesses get a 360-degree view of their audiences, understand how customers view and interact with the brand, increase brand awareness, improve customer acquisition, and more.

The pandemic has been a primary driver in disrupting digital marketing. Today, consumers look for highly-personalized content. The best Marketing, Sales, and Customer Support teams are all moving in the same direction: toward the customer. This means they’re also moving ever closer to each other with the common goal of targeting and landing specific accounts. However, convergence does not just happen. It requires planning, coordination, and a good bit of innovation.

Real-time marketing is the combination of behavioral analytics and automated marketing to provide customers with the right offer at the right time based on specific customer behaviors. Using what you know about an individual customer or segment, you can sense and respond at the moment to serve their needs. Real-time marketing analytics is a must-have in the world of digital marketing. Companies can make better decisions about where to allocate resources and how to adjust their marketing strategies on the fly when they track and analyze data in real-time.

Customer segmentation is the practice of dividing a customer base into groups of individuals that are similar in specific ways relevant to marketing, such as age, gender, interests, and spending habits. Today’s customers are savvy. They know that companies collect data on them, and they expect companies to personalize interactions with them as a result.

The stronger your analytics, the better your chances of delivering the right experience at every step of their customer journey through personalized interactions, making the right offers at the right time and tailoring experiences that go above and beyond expectations.

Predictive analytics is probably the hottest thing in marketing analytics right now. Predictive analytics go beyond describing consumer behavior to predicting how consumers will behave in the future based on data. Wouldn’t it be awesome if you already knew what your consumers wanted and when?

For that to happen, it is crucial to analyze consumer behavior to:

Predictive analytics leverage your data to predict who your ideal customers are. You can reduce the time you spend guessing who is ready to buy, and focus more time on closing new deals. You want customers who can really benefit from your business and are serious about engaging with your services. You can help more of your target audience find your business online by optimizing your marketing efforts for conversions. Predictive marketing enables you to identify the highest quality leads to pursue.

Predictive lead scoring is a data-driven lead scoring methodology that uses historical and activity data to identify the sales leads that are most likely to convert. Essentially, it analyzes data around successful leads (leads that became customers).

By crunching this data, predictive lead scoring:

• Identifies patterns and relationships that may never have been noticed before.
• Reduces the margin of human error in traditional lead scoring.
• Increase the amount of quality of leads.

Product-market fit is crucial to the success of any business. Predictive analytics help companies understand their market better so they can create a more effective strategy.

Predictive analytics make your marketing campaigns more customer-oriented and help you define your target better, by creating an effective predictive model that ranks the customers in your database according to who is most likely to buy, subscribe, etc.

Incorporating key findings that give you a deeper understanding of consumer trends into your marketing strategies can push you ahead of competitors in your industry.

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Customer personas are detailed representations of segments within your target audience. Fueled by data-driven research, they map the “who” behind the buying decisions of your products or services. Understanding your target audience requires you to find out what they do, who they are, their motivations, behaviors, etc.  Marketing analytics tells you all of this information and more. Insights from customer personas can help improve copy, tailor targeting, and inform product development.

Segments in Google Analytics can showcase the on-site behavior of key customer groups. Create segments for:

• Average revenue per user.
• Transactions per user.
• New versus repeat customers.
• Frequent customers.

A recommendation engine is a type of data filtering tool using machine learning algorithms to recommend the most relevant items to a particular user or customer.

How does it work?

Step 1: The first and most important step is to gather data.

Step 2: Once the data is gathered, it needs to be stored.

Step 3: To be used, the data must then be drilled down into and analyzed (Real-time analysis. Batch analysis. Near-real-time analysis).

Step 4: The final step is filtering. The outcome of this filtering is the recommendations.    

There are three main types of recommendation engines:

“Likelihood to buy” is the golden opportunity that all marketers want to get a good handle on. With the help of smart data and predictive analysis, you can determine which individuals are likely to buy a car, take out a private loan, or become parents in a given period. In short, you can identify consumers that are moving into a new phase of life with new needs, interests, and buying behaviors.

Using predictive techniques guided by machine learning and artificial intelligence, predictive modeling helps assess future customer behaviors by identifying patterns and similarities between variables in the data. The huge advantage better-quality buyer personas give to brands is that more detail allows them to create well-tailored offers to reach the right buyer at the right time with the right message.

Marketing analytics help you optimize your campaign by:

• Providing a 360-degree view of the customer journey and helping you understand their needs, desires, and the path to purchase.
• Delivering insights for targeting the ideal audience by identifying the characteristics your best customers have in common.
• Letting you create a personalized customer journey that’s precisely designed for each segment, enabling you to send the right message via the right channel at the right time.

Channel optimization refers to techniques used to increase KPIs across all of your marketing channels. As you build your channel optimization strategy, you’ll test a number of variables in your campaigns to determine which ones are most successful, then scale those across the program. By analyzing the performance of each channel and platform - including social media, email, websites, smart TV, and direct marketing - you can identify which are performing best for any given market segment and customer journey point. Based on this data, you can reallocate spending and improve ROI.

Interactive data visualization is the use of tools and processes to produce a visual representation of data that can be explored and analyzed directly within the visualization itself. This interaction can help uncover insights that lead to better, data-driven decisions.

Marketing teams can utilize data visualization in almost all phases of outreach, including processing data that has been collected, creating a marketing strategy, and analyzing the performance of the marketing strategy.

Four ways marketers use data visualization to their advantage:

1. Conversion of Complex Data into Digestible Format Creating Customer Profiles.
2. Analyzing Marketing Strategies.
3. Assess and Improve the Performance of Various Platforms.
4. Improve Website Conversions.

Marketing report automation is an integral part of a healthy analysis process. Marketing reports are the way to monitor the effectiveness of your advertising efforts and the value generated by your campaigns. Business intelligence solutions offer broad calculation and visualization features.

Some of the benefits of report automation for marketers:

• Data granularity.
• Faultless data.
• Higher frequency of reports.
• Higher focus on primary tasks.

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Content marketing is designed to distribute informative and consistent content tailored to your buyer persona. The content is geared towards answering the pain points your buyer persona suffers. It addresses these needs in a way that attracts and engages your audience.

Data-driven content marketing is an analytics approach used to optimize marketing strategies. Data is collected from a targeted audience that matches a company’s customer profile or buyer persona. Data-driven content marketing uses real data acquired through customer feedback and interactions. This feedback gives you insight into buyer motivations and their preferences as it analyzes their behavior online. Data can also provide feedback on who is interacting with trending topics. This approach highlights what channels your target audience is currently using. It also enables you to identify the most relevant influencers within these groups. Data-driven content marketing strategies ultimately help companies optimize how a marketing channel performs.

According to research, 84% of companies that work to improve customer experience report increased revenue. Using advanced data collection, analysis, and visualization, you can determine the quality of your service directly through interaction with your users. The combination of AI and data will enable you to gain attention and build trust in real-time, resulting in increased sales and brand awareness.

4 ways to maintain real-time customer experience:

1. Improve the average response time.
2. Align content with customer needs.
3. Allow cross-channel communication.
4. Enable customer support at all hours.

A positive customer experience is crucial to the success of your business because a happy customer is one who is likely to become a loyal customer who can help you boost revenue. Marketing analytics provide valuable insights that enable brands to make data-driven intelligent decisions, potentially improving consumers’ shopping, support, and service experience. The improved customer experience often leads to better customer sentiment, sales, and earnings.

Business intelligence transforms crucial facts from a vast amount of unstructured data into actionable information that enables companies to make informed strategic decisions faster than ever, improving operational efficiency and business productivity. Business Intelligence helps companies make informed decisions on strategic issues by providing crucial information on the current and historical performance of the company along with future trends, expected demands, customer behavior, etc.

Every company possesses data that has been poorly classified or is uncategorized (dark data). This can cause security breaches which can result in a loss of reputation and clients. With marketing analytics, you'll be able to take control of your dark data. And by doing so, you limit the potential for costly security threats.

Business Intelligence is not a new thing, it has been around for several decades. But now thanks to the convergence of data science and AI, data can be pulled together and combined automatically, so teams can leverage more data, produce more models, and answer business questions that were previously not possible. The impact this has on marketing is massive. For example, you can create marketing campaigns specifically for your target audience thanks to all the data collected.

Marketing analytics brings many different benefits to businesses. Here are some of those benefits:

Only about five years ago, data preparation took up to 80% of the time dedicated to a data project. In 2020, data scientists spent about 45% of their time on data preparation tasks, including loading and cleaning data. While this is a significant improvement, data preparation remains a time-consuming step that needs to be optimized to scale AI across the organization and complete more projects faster. Marketing analytics together with AI will keep getting better and more efficient, helping data scientists save more time.

Managing effective relationships with customers has become increasingly important in the era of constrained resources and global competition. All customers expect to be treated well and made to feel important. In addition, building customer relationships that will last takes time and a deep understanding of their needs and desires. Business Intelligence allows companies to know their customers better than ever before, which allows them to create personalized marketing efforts, thereby enhancing the level of happiness and satisfaction customers experience when interacting with the company.

Business enterprises that depend on real-time data collected from varied sources need to generate real-time actionable insights to gain value from the data. Marketing teams used to spend days going through non-standardized business reports. By implementing business intelligence in sales and marketing, you can reduce report generation time from days to a matter of hours.

Also, product companies can now maximize their revenue generated from every dollar spent on advertising or marketing campaigns. Business intelligence tools can be used to measure how customers are responding to your sales campaigns and allocate more resources to the more successful campaigns.

Business Intelligence and marketing analytics are democratizing the use of analytics. Not long ago, you needed to be a data expert to understand it. Nowadays, with the advances in technology, anyone can understand their data and take action based on it.

The biggest challenge marketing teams face is to give customers exactly what they want and when they want it. Or better, when they need it. With marketing analytics bringing accurate data this task has become easier than ever. Marketing analytics are also easily scalable throughout your business journey thanks to the power of automation.

Businesses need access to real-time and near-time operational data to be agile and respond quickly to changing market conditions. Reducing data latency allows organizations to make business decisions faster and more accurately.

With new technologies and new tools being released, every day it's easier to understand, work with, analyze, and create data. This gets businesses powerful benefits like improved decision making, innovation, productivity, customer and employee experience, and more.

Marketing analytics adoption is growing year after year. Every day, more businesses are realizing their power and leveraging their data to grow and scale. If you haven't yet, it's time to get your feet wet. Dive deep into the world of marketing analytics and take your business to levels you couldn't even imagine before. Don't worry if you are not tech-savvy, we know all of this information can seem impossible to understand for some people. That's why Narrative BI was created in a way that everyone (even the most beginners) can understand their data and start making data-driven marketing decisions quickly. Best part? You can start for free.