A Guide to Marketing Analytics
Marketers are always trying to improve, grow, and reach more customers. What’s the best way to do that? Well, you certainly have to start with a great product or service, but you also need data. Data analytics in marketing tells you what’s working, who your customers should be, and where to focus your marketing resources.
The marketing skillset doesn’t usually include number crunching, but it does include understanding and acting on a range of marketing analytics in order to maximize a marketer’s time and the company’s resources.
What is marketing analytics?
Marketing data analytics is the use and study of data related to marketing activities. Data analytics in marketing is used to determine the success of past campaigns in terms of ROI, conversions, customer behavior and preferences, and organic traffic. By analyzing the data regarding past campaigns using marketing analytics, marketing departments should be able to use patterns or trends to improve activities, resource allocation, and campaign planning.
The marketing data analytics sphere usually includes three components: analyzing the present, reporting on the past, and predicting for the future.
- Analyzing the present: Marketers need to assess marketing analytics from current campaigns and activities in order to get a clear picture of where the marketing activities stand and to compare them to past campaigns. In this case, they’ll be focused on website traffic and sources for it, social media engagement and click-throughs, as well as the current state of the sales pipeline and revenue metrics.
- Reporting on the past: Marketing departments also rely on reported marketing data analytics at the completion of campaigns, focusing on information such as lead conversion, customer lifetime value, and sales funnel churn rate.
- Predicting for the future: Finally, marketing departments rely on marketing analytics to plan future projects. This type of data analytics in marketing will include lead scoring, targeted content distribution, and upselling readiness and relies on datasets as well as modeling and AI.
Why is marketing analytics important?
Marketing analytics gives marketers the insights they need to plan successful campaigns and carry out activities that will help them reach their strategic goals. Without marketing data analytics, marketing departments would be reliant on guesswork or anecdotal evidence to make choices about how to spend the budget, what channels to use to promote their brand, and what customers to target to reach the best outcome.
Who uses marketing analytics?
Every member of the marketing team can use some form of marketing analytics. When the chief marketing officer and top-level managers are putting together the company’s marketing strategy, they’ll use marketing data analytics to design the right strategy. When a marketing manager is putting together the marketing plan, they’ll use marketing analytics to determine which channels should receive the most focus when it comes to content distribution. When an SEO specialist is creating a plan for keyword optimization, they’ll use marketing analytics to choose the correct keywords to include and important competitor behavior.
In short, every marketer can benefit from using data analytics in marketing if they take the right actions based on marketing analytics information.
What actions can you take based on analytics?
Marketing departments can take an almost unlimited number of actions based on marketing analytics, but this is a selection of some of the more common options:
- Incorporate keywords: Marketers can use keyword analytics software to determine the specific words and phrases they need to optimize in order to gain organic traffic through web searches.
- Replicate successful campaigns: Social media data analytics in marketing (there are often basic versions built into each platform) can give marketing departments an understanding of what types of content or topics resonate with followers and result in traffic to the website or newsletter sign-ups. Marketers can then increase that type of content to increase traffic.
- Engage new markets: Marketing departments can engage with a new segment of the market or launch a campaign that targets a different demographic if analytics show prospective customers in those areas.
- Optimize CRM: Agencies can also address bottlenecks in customer relationship management as marketing analytics are included in those platforms to help assess funnel and churn.
- Adjust product fit: Because marketing departments can access behavioral, purchase history, and website journey data for customer bases, they can better predict customers’ needs and purchase preferences.
Marketing departments have a range of marketing analytics tools and software at their fingertips. They should be using as many of those as are appropriate to improve marketing activities and plans every day.
Introducing B2B marketing analytics
B2B and B2C marketing are similar in many ways, but they are also quite different. B2C marketing involves appealing to a customer’s emotional reaction with the transactional goal of them purchasing your product or service. On the other hand, B2B marketing involves building brand recognition and relationships that can turn into leads to generate sales.
To that end, B2B marketing analytics relies heavily on keyword analysis, target market data, lead generation, lead scoring, and optimizing the lead-to-customer ratio. One basic element to consider with B2B marketing data analytics is using data to get a better picture of the specific demographic of your target audience, which will likely include one or more decision-makers at a company. Using keyword analytics as well as Google Analytics, the marketing team will be able to get a broad understanding of the branding required for this audience.
Marketing analytics can help B2B marketers determine the optimal top-of-funnel prospective list, as well as the most successful forms of repeated communication.
Important concepts within marketing analytics
Certain concepts within marketing analytics can be critical to maximizing efforts and resources. These important concepts within marketing analytics can mean the difference between an average marketing team and one that truly excels in research, planning, and execution.
- Customer lifetime value (LTV): Marketing departments can use predictive data analytics in marketing to determine the customer’s lifetime value to the company based on past purchases, purchase frequency, and average customer lifespan. This allows them to make predictions about future ROI and customer engagement.
- Return on investment (ROI): In marketing terms, analyzing ROI refers to the amount of profit or revenue growth that can be attributed to marketing activities. Capturing this ROI data gives companies another metric for marketing teams’ success.
- Cost per lead: To determine how cost-effective a campaign is, a marketing department must understand the cost per lead data. Cost per lead refers to the average cost for generating a new lead. Cost per lead can be used to help calculate the marketing ROI.
- Lead-to-customer conversion rate: Another metric marketing analytics can help measure is the lead-to-customer conversion rate or the percentage of leads that resulted in sales. This type of data can help direct marketing departments to increase marketing that generates specific types of leads that are proving most successful in converting to sales.
How to choose marketing analytics software
Choosing marketing analytics software can be difficult because there are a lot of options on the market. It might seem like you need a different tool for every metric you’d like to measure (though that isn’t always the case).
Wrike can import metrics for up to 50 different digital marketing tools, helping you streamline your workflow and take your marketing to the next level. Learn more about how to choose the right marketing tools and software in our guide.