For decades, marketing used to be a trial-and-error method. The more important the work, the higher the expense. Thus making marketing quite expensive. Organizational management is willing to invest in this area. But they need a solid plan and good results from it. Marketing ROI measures the impact of marketing initiatives on profit and revenue growth. Senior executives insist on accurate measurements demonstrating value to organizations.
The job of a marketing analyst is to understand the data driving marketing decisions. Marketing analytics is turning data into insights that inform marketing strategy. In other words, marketing analytics is all about using data to understand what is and is not working in your marketing campaigns.
Contents
- What Is Marketing Analytics?
- Importance of Data
- Gathering Data for Marketing Analytics
- Dealing With Streaming Data
- Data Storage
- Marketing KPIs
- Marketing Revenue Attribution
- Customer Acquisition Cost
- Customer Lifetime Value
- Digital Marketing ROI
- Traffic-to-Lead Ratio
- Types of Marketing Analytics
- Analytics Models for Marketing
- Successful Marketing
- Conclusion
What Is Marketing Analytics?
Marketing Analytics is conducting data analysis for marketing reasons. Data is collected both online and offline. This includes data on clicks, website usage, and marketing responses. They use tools like beacons, point-of-sale (PoS) transactions, and data gathered through surveys. Marketers also collect data from a variety of digital touchpoints. Even if they don't interact with their clientele, they do so through webinars and other events.
Organizations can use marketing analytics to measure the success of their promotional efforts. It also helps in advertising campaigns and client interactions across all channels. A structured framework can test each endeavor's strategic returns, worth, and payback period. As a result, analytics show underperformance, overspending, and the demand for a service.
Importance of Data
The organization uses data to make decisions on how to run its business. Organizations continue to learn about their target audience over time. Campaigns are successful with proper knowledge about how customers interact with the brand. Analyzing this data will improve the campaigns and result in the generation of leads. Over time, one can convert these leads into customers.
Analytics refers to the tools and methods used by marketing teams to improve their work. One can use marketing analytics to measure the effectiveness of campaigns. KPIs for marketing analytics include website traffic, audience analytics, and ad performance. Marketing analytics reveals how marketing initiatives affect sales and product acceptance. This will provide context for how users discover the product or service.
Gathering Data for Marketing Analytics
Every venture can succeed with correct information. One should gather first-hand information from their primary collection touchpoints. They should consider second and third-party sources to enable comprehensive analytics. Marketing analytics enables one to know how to increase the value and relevance of data sets by enhancing and modifying them. An essential part of marketing analysis is how to gather data.
The first step in any marketing analytics project is to collect data. This data can come from various sources, including website traffic data, social media metrics, customer surveys, and sales data. Once one has collected this data, one needs to clean it and organize it so it can be analyzed.
Gathering Customer Data
Data from customers is essential for all marketing analytics. Gathering customer data through loyalty programs, surveys, and gated assets is effective. One can encourage customers to identify themselves when they store their data. The initial step is to get the first-party data. To identify prospects, businesses must collect online behavioral data.
Companies can link individuals' browser IDs or cookies to other first-party data. Users disclose information when placing a code on their website or media pages. Businesses can leverage consumer feedback from forms, surveys, and other means of contact. Capturing data in a CDP or CRM system can help define audience segments. Doing so will allow businesses to retarget customers and prospects in marketing campaigns.
The data gathered from customers fall into three categories.
- Customer Data: This includes gender, address, financials, and other information.
- Transaction Data: One collects this via the web, PoS purchases, or other conversions.
- Engagement Data: One collects personal data via campaigns, loyalty programs, and other forms.
Data collected from customers, site visitors, and social media followers is first-party data. Data from organizations that help customers communicate can enhance companies' data. Utilizing third-party data to offer extra demographic details might help businesses improve segmentation.
First-party data is ideal for remarketing, projections, and predicting behavioral trends. This is because it reflects customers' direct interactions with the company. Data from second and third-party sources can help with these initiatives. However, third-party data is more expensive to get and integrate than first-party data. Thus, one should focus on first-party data. They already have access and authorization to use it. Also, one should consider using second and third-party data to supplement and fill in any gaps.
Gathering Product Data
Enforcing consistency in product data is essential. It is vital for advanced analytics and data science initiatives. Data science also deals with subjective attributes. Here again, one has to be consistent in defining these attributes. Corporations have limited contact points with customers. Customers can learn more about products through various channels.
For example, customers may proceed from an email to a product listing. Someone else could find the listing on the internet. A Google search may bring a third customer to the product, and an Instagram ad may get a fourth. Create regionally-specific landing pages and online stores to serve visitors at various touchpoints.
Gathering Company Data
B2B marketers must create account profiles for organizations rather than individual buyers. In these cases, people refer to customer data as "company data." Marketers attempt to understand the structure of these prospective organizations. They try to understand how their products and services appeal to different people. Marketers know who controls sales decisions as part of the marketing process. In most scenarios, marketing participates in the early stages of the buyer's journey. They encourage product trials before contacting the buyer to close the sale.
Dealing With Streaming Data
Streaming data often arrives, and the total volume can escalate. This data is often ingested and updated in "near real-time," such as every five minutes. Data may be easier to analyze if aggregated first. Hotels and theme parks use real-time IoT data for in-progress customer targeting. Low-energy devices broadcast messages via Bluetooth or Wi-Fi on RFID-enabled wristbands or apps. Marketing analytics combines data from various touchpoints to enhance the customer journey.
Data Storage
Inconsistent data is a significant issue for most marketing organizations. For example, a long sales cycle is a characteristic of some industries. Also, many people may be responsible for each customer.
This may present a problem. Leads to reports make obtaining the much-touted "360-degree view" of the customer easier. Businesses use data warehouses, data lakes, or cloud data platforms to increase flexibility. It makes it easier to use data from many sources. For example, the data lake stores raw clickstream and weblog data, but the data warehouse stores aggregated metrics.
Businesses rely on cloud databases to store and analyze large data sets. This includes semi-structured as well as unstructured data sources. This information comprises website user clicks, browsing patterns, audio, visual, and other sources. In addition, businesses use cloud-based databases to scale up operations and focus on business intelligence.
Marketing KPIs
Proper marketing KPIs help identify which campaigns and tactics have the most significant impact. It determines whether one meets the sales and marketing goals. A company can adjust various strategies and budgets by tracking marketing KPIs. When setting and tracking marketing KPIs, many marketers and business owners pay attention to the usual suspects: sales revenue, the number of sales-qualified leads generated, and cost per acquisition.
As a marketing analyst, one constantly looks for ways to improve marketing campaigns and strategies. Marketing analytics is a great way to do this. By understanding what marketing analytics is and how it works, one can make better decisions that will lead to more successful marketing campaigns. Let's look at a few more KPIs one should track:
- Marketing revenue attribution
- Customer acquisition cost
- Customer lifetime value
- Digital marketing ROI
- Traffic-to-lead ratio (new contact rate)
Marketing Revenue Attribution
No company wants to spend money on something that does not generate a good ROI. According to Marcus Sheridan, author of They Ask, You Answer, "the only content that works is content that generates sales." One can use this to track and evaluate efforts. Several models can be used to track revenue attribution.
For example, single-touch attribution models consider website users' first or last interactions. One can also investigate multi-touch attribution models, which distribute deal credits across each touchpoint. Tracking this data allows the team to demonstrate the monetary value of their efforts. Understanding this metric is critical because it indicates how effective these campaigns are.
Customer Acquisition Cost
CAC considers the total sales and marketing expenditure required to get new customers. This includes programs, marketing expenses, salaries, and any overhead associated with leads becoming customers. One should calculate their CAC for both digital and outbound marketing. This allows them to see the full scope of their efforts and which ones are most effective.
When calculating this metric, one must consider the time frame they will test this cost. Once they've decided on a time frame, the following examples can help them calculate the total sales and marketing costs associated with digital and outbound marketing:
- Calculating CAC for digital marketing AND relevant expenses include:
- Human resources (sales, creative, and technical)
- Technology and software such as HubSpot, Vidyard, and Semrush
- General overhead
2. Calculating CAC for outbound marketing and relevant costs include:
- Advertising
- Marketing distribution
- Human resources (sales and marketing)
- General overhead
The writing should be as transparent as possible to address potential customers' concerns and questions.
Customer Lifetime Value
Customer lifetime value is how much revenue a business can expect over the average lifespan of a customer. The cost per lead drops if one can generate more revenue from existing customers. Thus, one can spend the marketing budget on better-quality prospects. One way to increase customers' lifetime value is by developing lead-nurturing campaigns. It has to reach out to existing customers. This will allow the sales team to inform existing customers about new services, products, and resources.
Digital Marketing ROI
Every company wants to see a return on its marketing investment. Analyzing monthly and annual performance necessitates calculating the digital marketing ROI. Planning strategies and budgets for future planning periods is also essential. Avoid increasing your marketing budget for a costly and ineffective campaign. As a result, regardless of the marketing strategy employed, the return on investment will determine how the company proceeds.
Traffic-to-Lead Ratio
Understanding the source of website visitors—organic, direct, social media-driven, or referred—is critical. There is a problem if the page's traffic is stable or increasing, but the traffic-to-lead ratio is low or falling. The most likely explanation is that the information displayed and what users thought they were clicking on do not match. They may also be served content that is inappropriate for them or does not address their concerns, forcing them to seek something that does.
A heatmap is a tool to include in a marketing report, especially for high-performing landing pages and blog posts. For example, one can monitor the website traffic-to-lead ratio to identify when it might be appropriate to modify the page copy, design, CTAs, or even the attached form.
Types of Marketing Analytics
Marketing analytics generally falls into two main categories: descriptive and predictive analytics. Descriptive analytics looks at past data to understand what has happened. Predictive analytics uses past data to predict what will happen in the future. Both types of analytics are essential for making informed decisions about future marketing campaigns.
However, predictive analytics is becoming increasingly important as we strive to personalize marketing messages and create more targeted campaigns. For example, we can use data about individual customers or prospects with predictive analytics to predict their behavior. This allows one to create more customized and compelling marketing messages that are more likely to convert leads into customers. Predictive analytics is also essential for detecting early signs of customer churn so that one can take action to prevent them from leaving.
Analytics Models for Marketing
Monitoring KPIs brings a difference in marketing data analysis techniques and models. The analysis of brand awareness uses distinct data and models. Some popular analytics models and methods include:
- Media Mix Models (MMM)
- Multi-Touch Attribution (MTA)
- Unified Marketing Measurements (UMM)
Media Mix Models (MMM)
MMM is a research method. It allows marketers to check the effectiveness of their marketing and advertising campaigns. It determines how different components contribute to the marketers' goals. The fundamental goal is to drive conversions. Using insights from MMM, marketers can fine-tune their efforts. They do so by basing themselves on various parameters to create a great campaign. As a result, their campaigns stimulate engagement and sales. MMM can test a broader range of traditional and digital media using total data. MMM allows marketers to account for external factors such as seasonality and promotions.
Multi-Touch Attribution (MTA)
The MTA is a method of measuring marketing effectiveness. It considers each stage of the customer journey. After that, it assigns a percentage of the credit for a conversion to each channel. Marketers can assess the impact of user-level events using various multi-touch attribution models. Each of these models scales advertising performance. Each advertisement depicts the purchasing process. Multi-touch attribution allows marketers to link sales to native advertising and email marketing. They also removed the failed display advertisement.
Unified Marketing Measurements (UMM)
UMM is a marketing analytics approach. It combines data and insights from different attribution models into one comprehensive measurement. This combination provides a complete picture of marketing campaign success and its conversions. Marketers can use suitable measures to optimize campaign marketing spending. UMM helps overcome obstacles. They correlate data from marketing mix modeling with person-level data provided by MTM. Marketers determine which messages work best with individuals by considering external factors.
Successful Marketing
Growing technical skills and a data-driven marketing approach are always in demand, especially in the area of marketing analytics. This is because marketing entails psychology, emotions, and communicating value propositions. It assists in identifying and quantifying behavioral aspects of the purchasing process. Marketers aim to gain insights into the patterns by which customers make choices. Marketers can use data sources like Google ads, Facebook, Google Analytics, page views, and CTCs. People in the field of marketing analytics can use these tools to track the performance of their products and services. For example, they can track engagement, views, and reviews from various media platforms.
How Analytics Can Help In Increasing Your Revenue
Conclusion
In conclusion, the definition of marketing analytics is: It is a powerful tool every marketer should use to make informed decisions about their campaigns. By understanding what it is and how it works, one can use it to take their marketing efforts to the next level. If one is not already using marketing analytics in their work, now is the time to start! Every little action taken in marketing produces data. Analysts can identify the most influential creative assets, content, and channels. One can plan, distinguish, and combine data from various sources, apps, and tools to do this.
Marketing analytics is a critical tool for any marketing analyst. By understanding the principles of marketing analytics data, one can provide valuable insights that can help improve marketing campaigns and drive results for their organization.
