As a B2B Marketing Strategy consultant, how can you use data to drive better results for your clients?

1- Focused on SQLs over lead quantity, increasing conversions by 20%. 2- Unified CRM and social data, boosting campaign engagement by 30%. 3- Data visualization revealed trends, leading to a 25% ROI improvement. 4- Implemented 14-day A/B testing sprints, enhancing click-through rates by 15%. 5- Targeted in-market LinkedIn buyers, resulting in a 40% higher lead quality. 6- Showcased a 50% customer retention increase in case studies, affirming strategy effectiveness. 7- Personalization using AI in B2B marketing is a key emerging trend for higher engagement and conversion rates.

While defining goals and metrics are helpful, one thing that is often lost is how the marketing metrics ultimately influences revenue. While having a goal of driving 300 leads from a campaign at $150 CPL is good to have, it's another thing entirely to have goals like bringing in X number of new SQOs. I believe that's why it is first mission-critical to make sure everyone in marketing first understands how the work they do attributes to revenue, and then let the revenue goals influence marketing campaign goals. This will not only allow for greater support with executive leadership but can also help bring further alignment between marketing and sales teams especially. Which reminds me: do be sure to talk with the sales team(s) while planning!

Choosing the right metrics to track is really important. Some think tracking lots of metrics is good, but it's better to focus on key ones—like how different channels perform, input-output measures, and so on. If you track a metric but don't use it to take action, it's a waste of time. Teams should pick metrics that they can actually use to make better decisions and understand things better. That way, they avoid spending time on metrics that don't really help.

B2B marketing strategy consultants use data to drive results by setting clear goals, defining metrics, and aligning KPIs. Data collection integrates CRM, automation tools, and analytics, facilitating customer segmentation and personalized targeting. Predictive analytics aids lead scoring and market trend predictions. Performance analysis, A/B testing, and customer feedback optimize campaigns. Competitive analysis informs market positioning. Regular reporting with visualizations ensures transparent communication. Adaptability and continuous learning foster agile strategies, delivering measurable outcomes for clients.

Establish clear, measurable objectives aligned with client needs. Identify key performance indicators (KPIs) that accurately reflect progress towards these goals.

While this seems like an obvious step, it is critical to make sure marketers are getting clear understandings of how your work is impacting pipeline. A CRM and marketing automation platform like HubSpot is of course necessary for accurately tracking your efforts, but there are now far more intricate tools like RevSure to help consolidate platforms and then even use AI to predict outcomes based on current trends. Platforms that are properly connected are necessary for monitoring performance and my personal hope is that we marketers level up in 2024 to better understanding our data, not just pointing to platforms like Google Analytics as a soul source of truth.

Gather data from various sources like CRM systems, website analytics, and social media platforms. Integrate this data for a comprehensive view, ensuring accuracy and consistency.

One thing that cannot be overstated here is that while having specific reports reviewed regularly is valuable, data and performance can vary for a multitude of reasons. This is why it's very important for us marketers to be thinking holistically about performance. If something looks "off" in the data, I think it's a valuable endeavor to explore that and look for reasons why it might be. Or in the inverse, it's important to look for data that might suggest things are performing "too well" and look for holes to uncover why that might not actually be true. All of the research should point back to answering our original focus of achieving revenue-driven objectives.

Use analytical tools to derive insights from the integrated data. Visual representations like charts and graphs help in understanding trends, patterns, and areas of improvement.

Campaigns that have data but don't result in action is meaningless. This is why we generally recommend for digital campaigns in particular running a Sprint Framework - a 14-day cycle where two variables are tested and then reported back on, with the outcome that changes will be made and performance will continuously improve. This type of framework is great for minor campaign types like testing landing page messaging, ad creative, audience targeting, etc. This framework won't work for all campaigns certainly, but building out this type of structure within a marketing team can have a huge impact on performance and get everyone aligned on always improving outcomes.

There are no set rules or best practices. I love testing and being creative. Don't just do what everyone else does. .That will lead to average results. Do something bold.. ridiculous even.. then test if it had a positive or negative impact. Repeat, test, measure, reiterate. Always test, or stay stuck.

Implement A/B testing to compare different strategies. Analyse results to understand what works best and continuously refine campaigns for optimal performance.

Leads are great and all, but what about SQOs? If you have great campaigns that are driving leads but not bringing in revenue, is that a successful campaign? Perhaps. I would argue though that all marketing objectives should tie back to business (and preferably revenue) goals. While it's important to bring in leads generally, especially for companies with long sales cycles, at the end of the day marketers are responsible for influencing people to make purchases. Leads could do that through effective nurturing strategies, but LinkedIn has identified at 5% of buyers on LinkedIn are in-market for a product or service at any given time. Let's make sure we're capturing that market first before going after the other 95%.

Utilize data to identify potential leads and understand their behavior. Tailor marketing efforts to guide them through the sales funnel effectively.

Focus on KPIs that indicate progress in the B2B buyer journey, such as the impact on sales pipeline creation, cost per proposal, meeting, and sales qualified lead. This long-term view is essential for successful B2B marketing. For short-term insights, analyze direct searches, brand-related searches on Google Trends, and website demographics using tools like Dreamdata, Lead Forensics, and Leadfeeder. Utilize LinkedIn advertising data for quantitative analysis on customer reactions to different messaging, informing strategies for website content, newsletters, and sales approaches.

Use data to track the return on investment (ROI) and other metrics that demonstrate the value provided to the client. Present data-driven reports to show progress and results.

Stay updated with data privacy laws and ethical considerations. Also, invest in training to keep up with the latest data analysis tools and techniques. Remember, the goal is not just to collect data, but to use it to inform smarter marketing decisions.