What are the best practices for using marketing analytics to inform your content strategy?

Not all pieces of content are created equally. By understanding what the audience is for this piece of content, you can then adapt your goals to measure realistic actions taken from that content. An example of this might be a listicle blog of top 10 washers for [Year]. I know that if my product has a high price point, most likely this blog isn't going to convert from a transaction perspective, BUT I can realistically track and see how many of the products were viewed by users after/while reading the blog. By narrowing in on that, I can then provide VALUE to my clients by communicating how many added product views are being driven on their website by the efforts of our SEO team and the content strategy we are running for them.

I like to catalogue all existing content, and map each piece to the buyers journey. So top of funnel content, middle of funnel content and bottom of funnel content. I then put a time stamp on each piece and label what type - blog, webinar, ebook, solution brief, case study etc. I then look at metrics for each one - downloads, views, registrations, views etc. I maintain this catalogue over time. This way we can view the performance of each piece, and look for patterns with the top performing content that we can replicate. It is a great way to find content we can re-purpose. Last, I look to establish a content strategy based on a mix of content we believe addresses the major pain points of our ICP and target buyer personas.

Include micro-conversions, while it's essential to track major conversions like leads and sales, don't overlook the smaller steps that lead to them. Think of micro-conversions as the incremental actions your audience takes on their journey. These could include signing up for your newsletter, downloading a resource, or spending more time on your website. By setting goals and metrics for these micro-conversions, you gain insights into how well your content nurtures prospects through the sales funnel.

Defining a learning agenda with SMART goals and aligned metrics is vital for a successful content strategy. It brings clarity, measurability, achievability, relevance, and time-bound focus to your objectives. This customer-centric approach ensures adaptability, enabling you to create impactful content at every stage of the customer journey and make data-driven improvements when needed. In essence, it acts as a roadmap for your strategy, guiding efforts, promoting accountability, and facilitating continuous improvement. Without it, content creation lacks direction, making impact assessment and adjustments challenging.

The market is your number one feedback tool. If you are not getting engagement, your content is not interesting or it does not provide value. If your content is not getting views, there could be an optimization issue or you are simply not using the platform as intended.

Consider embracing AI-driven data curation. Picture an AI companion that collects and curates data tailored to your needs, ensuring precision. It operates 24/7 for real-time insights, integrates seamlessly, and prioritizes security. AI guarantees consistency and data uniformity. With AI, you're not just analyzing data; you're orchestrating marketing success.

For me the basics are google analytics to monitor what my website visitors are reading on my blog (will take top content and try and further optimize to get higher search ranking), google console to tell me what queries are they using (terms, keywords) so I can better optimize my content to match their search (also will help with search ranking)....AB testing tools like VWO or CrazyEgg to tell me which versions of my homepage, other pages, etc. work better based on scrolls, conversions, etc...and again Google Analytics to tell me about conversions in general on my website so I can improve (it also needs to be connected to AB testing software for the same).

Reading "AI is the answer"-answers. LOL. I recommend getting hands dirty to understand your business, rather jumping on a hype wagon. In my opinion, the tools to collect/analyze data are in most use cases trivial, if you have proper labeling, tags, UTMs. However if much of your traffic comes from organic search, referral and offline, I recommend: Google Analytics+Hubspot page view/activity tracker, GSC+Ahrefs (to double check which search keywords are driving traffic, and where you can expect more in the future). Any other CRM will do to I would think. The link to your actual revenue/conversions/customers will provide to be super useful.

Research tools/services and testing capabilities should not omitted from this list. Google Trends can help identify opportunities if you're just establishing your business or have little traffic to leverage.

I would prioritize tools and sources that not only serve my current needs but can also scale with my business as it expands. It's easy to select tools based solely on your current budget and requirements, but as your business evolves, your data needs will too. Look for analytics platforms and sources that offer flexible pricing models and can accommodate larger datasets, more users, and advanced features when your business reaches that stage. Scalability ensures that you won't outgrow your analytics tools and need to undergo a disruptive transition as your business grows.

I tend to look more closely at psychographic segmentation. While demographic segmentation (age, gender, location) is important, psychographic segmentation delves deeper into your audience's psychological characteristics, such as their values, interests, beliefs, and lifestyle. By understanding the psychological drivers behind consumer behavior, you can craft content that truly resonates.

Segment and personalize data by categorizing your audience based on demographics and behavior. Use CRM systems to manage this data efficiently. Automate tailored campaigns with personalized messages and content. Implement website personalization and gather feedback for continuous improvement. Enhance customer engagement and ROI through data-driven strategies.

Personalize by buyer persona. Step 1, for B2B define who your ideal customer segments are, and then define the key buyer personas within them. Different personas relate and engage with content and CTAs differently. You can then use platforms like HubSpot to automate strategic buyer journeys based on each persona, so your content is relevant, engaging and adds value.

While segmentation and personalization are powerful tools, it’s crucial not to box yourself in too tightly. Over-segmenting could inadvertently alienate a potential target segment you haven’t considered. Many brands have discovered new audiences they never anticipated and have even revamped their core brand elements to cater to these new segments. Always leave room for expansion; you never know who your brand might resonate with next.

Segmentation and personalization are indeed powerful tools in the marketer's arsenal. They allow us to tailor our messaging to specific audience segments, enhancing relevance and engagement. However, as with any tool, it's essential to exercise caution. Over-segmentation can lead to a fractured and confusing customer experience, where individuals receive conflicting messages. On the other hand, over-personalization can raise ethical concerns and intrude on privacy. Finding that sweet spot where we deliver personalized content without overstepping boundaries is the key. It's crucial to prioritize transparency and consent in data collection and personalization efforts.

I've found emotional resonance test quite helpful in assessing and optimizing content. Here's how it works: Create variations of your content that target different emotional triggers. For example, one version might aim to evoke a sense of excitement, while another emphasizes trust and reliability. Then, measure the emotional responses of your audience through sentiment analysis, surveys, or even facial expression recognition tools if applicable. By understanding which emotional triggers connect most effectively with your audience, you can fine-tune your content to generate stronger emotional engagement.

Keyword research is so crucial. It will identify content gaps once compared with the analytics of each page. By understanding bounce rates, exit rates, and time spent on site, we can get an understanding of what visitors are looking at and what's missing from our content. Content can be added after that to address those gaps.

It's so important to run tests in a controlled manner over a reasonable amount of time to ensure that changes have passed learning stages. Overlapping tests naturally blur the lines of why data may have fluctuated. While it's easy to get excited and want to run multiple tests at a time, the best way to set your campaigns up for success is to run one test at a time and leveraging the best performing variation(s) to guide future optimization strategies.

I find this method most helpful. It is easy to analyze and create based on your results. It also allows you to go deeper on the topics and content that was well Recieved.

Leverage marketing analytics for content optimization with these best practices: Testing Methods: Use A/B, multivariate, or split testing to experiment with content elements. Data-Driven Decisions: Measure changes' impact on key metrics for informed decision-making. Continuous Monitoring: Stay updated with evolving content performance over time. Iterative Approach: Make incremental improvements based on analytics insights. Segmentation: Tailor optimizations for different audience segments. Goal Alignment: Ensure content changes align with marketing objectives. Record Keeping: Maintain records for historical context and learning. Collaboration: Foster teamwork between marketing and analytics teams.

Some best practices... Know Your Audience: Tailor content to their knowledge level. Visualize Data: Use charts and graphs for clarity. Storytelling: Craft a compelling narrative around data. Simple Language: Avoid jargon; keep it clear. Highlight Key Findings: Emphasize crucial insights. Context: Explain data collection context. Visual Aids: Use images and examples. Interactivity: Create engaging presentations. Ask for Feedback: Encourage questions. Follow-Up: Assess insights' application. Transparency: Be honest about data sources. Ethical Standards: Respect privacy and regulations. Conciseness: Focus on key takeaways. Team Training: Train your team for consistency

From My Experience: 1- Benchmarking: Always show competitor and comparative time progress, especially when presenting to management. This context enriches the understanding of your performance. 2- Actionable Insights: Make your data actionable. Always tie it back to strategic objectives and provide clear recommendations. 3- Review and Update: Trends change, and so should your reporting. Periodically review your communication strategy to ensure it remains effective and relevant.

Marketing analytics isn't just about numbers; it's about storytelling. Dashboards, reports, and infographics turn data into compelling narratives. Educating, informing, and persuading with insights is the key. Transparency is paramount. Honest data sources, methods, and limitations build trust. Upholding ethical and legal standards is essential. It's the bridge between data-driven decisions and credibility. ???????

In my experience, the generated insights must respond to a clear question and be aligned with the KPIs. Are the actions I am taking to generate more (insert objective) really working? This is especially crucial from an agency perspective. Clients not only need to know the performance and all comparison options but also the explanation of why a trend is positive or, at times, not ideal. This way, you can have a greater capacity for reaction and optimization.

However displayed, IMHO every data analysis needs to have 4 characteristics. I rank them by how difficult they (seem) to be provided on a daily basis: 1. dimensions (x/y) and breakdown - easy 2. development over time - easy 3. relative to budget/plan/competition - medium (most out-of-the-box dashboards cant do it, as you have multiple data sources - so I still love a good spreadsheet here) 4. flagged/explained outliers/anomalies/data quality issue

DON'T DO THIS! I've seen companies with 2 separate Google Analytics accounts. 1 for the company's website and 1 for their B2B application. Now the registration page for new customers / free trials, was in their app and NOT on their website. BUT the "Free Trial" button that took visitors to this registration page was on the website! You probably realize what the issue is. The "conversion" of clicking "Free Trial" on website had no data to show what actually happened. Did the visitor fill in their details and start a trial, become a customer?! We cannot know because the GA account on the app doesn't show where visitor came from as it's disconnected from the website and vice versa. > Make sure you have 1 Google Analytics across related assets.

Utilize marketing analytics to inform your content strategy by firstly defining clear goals. Leverage tools like Google Analytics to track website traffic, user behavior, and popular content. Use social media analytics to understand audience engagement and preferences. Employ SEO analytics to optimize keyword performance. Analyze customer feedback and preferences. A/B testing and heatmaps offer valuable insights. Regularly review data, adapt content based on analytics, and stay updated with market trends. By aligning analytics with your content strategy, you can create data-driven, engaging, and effective marketing campaigns.

Survey your customers/newsletters/Linkedin audience regularly on content they liked, or would like. 7-8 feedbacks will already tell you 80% of what you need to know. So, I can recommend: consider picking up the phone and talk to some real people.