The way that Customer Marketing teams and functions should be staffed and organized will vary greatly from company to company, especially when looking at more traditional B2B or sales-led organizations vs Product-led organizations. In my experience, though, the best way to orient the team is around three core responsibilities: * Activation & Engagement: Measurement of activation metrics and time to activation, often in the form of lifecycle marketing. Driving customer education and programmatic communication that support enterprise onboarding, end-user training materials, and aircover to gain as much traction within paying accounts as possible. * Upsells & Expansion: Driven through targeted programs that aim to increase revenue from existing enterprise accounts through targeting new teams, referrals, and surfacing new MQLs to account managers. Can be done through Customer Advisory Boards, 1:1 Account Events, Customer Webinars, and account-based acquisition campaigns. * Advocacy: Measurement of output-based programs that develop champions and put your customers on a stage like case studies, referencable logos, and customer stories across channels (webinars, events, content). When first starting out or when you have a lean team, I've found starting with an account-based customer marketing approach is the best way to drive meaningful impact and quick wins for your CSMs and on your company's bottom-line. Identify the top renewals or any accounts at risk of churning and create targeted account plans to save and expand each. This will provide the frameworks and structures to scale as the team grows.

I have one question that I love to ask in all of my in-depth interviews: "What is the challenge you are looking for at your next opportunity to help you grow to the next level in your career?" The best answers are those that sound intentional, thoughtful and deliberate. "I want to grow in my ability to do (x), and through this role, I'll be able to take on challenge (y) to help me get to the next step on my career path to (z)."

Incorporating experimentation and A/B testing into growth marketing strategies is key for driving sustained growth. Without it, marketing results often plateau quickly. Here’s a 6-step process I’ve used in the past to structure a conversion rate optimization program around. Step 1 - Hypothesis Formation In this initial step, pinpoint crucial variables that influence user engagement and construct hypotheses regarding potential changes and their outcomes. * Identify Key Variables: Recognize the key variables (like webpage layout, email subject lines, ad creatives) that you think have a significant impact on user engagement or conversion. * Develop Hypotheses: Formulate hypotheses based on your observations, analytics data, or customer feedback, predicting how changes in these variables might affect the outcomes. Step 2 - Designing Experiments Here, the focus is on developing different variants based on the formed hypotheses, establishing a control group, and setting up appropriate analytics tools to track the performance metrics accurately. * Creating & Develop Variants: Create different variants of the webpage, email, or ad, incorporating the changes as per your hypotheses. * Control Group: Maintain a control group where no changes are made, to compare the results with the variants. * Define Key Metrics: Set up key metrics (like click-through rate, conversion rate, etc.) that will help you evaluate the performance of each variant. * Setting Up Analytics: Ensure that analytics tools are set up correctly to accurately track the performance metrics. Step 3 - Conducting Experiments During this phase, conduct the experiments by segregating the audience into different groups and launching all variants simultaneously to avoid time-based biases, ensuring a fair test. * Randomized Split Testing: Divide the audience randomly into different groups, each group being exposed to one variant. * Simultaneous Launch: Launch all the variants simultaneously to prevent any time-based biases from affecting the results. Step 4 - Data Collection and Analysis This step entails meticulous data collection and analysis to discern the most effective variant, followed by deriving insights to comprehend customer preferences and documenting the findings for future reference. * Collect Data: Gather data on how each variant performed based on the defined metrics. * Analyze Results: Analyze the data to find out which variant performed the best and if the differences are statistically significant. * Draw Insights: Draw insights from the experiment results, understanding customer preferences and behaviors. * Document Learnings: Document the learnings from each experiment to build a knowledge base for future reference. Step 5 - Implementation and Optimization At this point, your focus is implement any successful test, engage in continuous optimization based on the learnings, and accelerate growth by repeating the testing process with new hypotheses. * Implement Changes: Implement the changes based on the winning variant to optimize your marketing strategies. * Continuous Optimization: Use the learnings to continuously optimize and improve your marketing strategies. * Scale Successful Experiments: Scale up the successful experiments to a larger audience to maximize the benefits. * Iterative Process: Make experimentation an iterative process, continuously testing new hypotheses to foster growth. Step 6 - Knowledge Sharing Lastly, foster a data-driven culture within the organization by sharing the learnings with the team, encouraging collaboration, innovation, and developing a flexible marketing strategy adaptable based on the insights gathered from the experiments. * Share Learnings: Share the learnings with your team to foster a culture of data-driven decision-making. * Collaborative Approach: Encourage a collaborative approach where team members can propose new hypotheses for testing. * Fostering Innovation: Foster a culture of experimentation within the organization, encouraging innovation and agility. * Adaptability: Develop an adaptable marketing strategy that can pivot based on the insights from the experiments. By following this structured approach to experimentation and A/B testing, you can effectively incorporate them into your growth marketing strategies, driving improved results and fostering sustainable growth.

I'd recommending focusing a lot more on engagement and less on lead generation or MQLs. In general, you should know the people you want to engage in each account, and you'll have them already populated in your CRM. This completely eliminates the need for any "lead source" tracking to prove effectiveness. Additionally, you'll want your team to keep engaging the important few until they're ready to take the next step with your company, so measuring actual engagement with marketing materials/programs is key. Several tools out there help with this such as Demandbase and 6Sense, but it can also be homegrown if you have the appetite for it. If I were to oversimplify a lot, assign points based on activities, roll them up to the account level, ensure they decay over time, and then set thresholds based on what matters most for your business. Maybe you need a lot of engagement within a few key contacts, maybe you need the whole village to get activated! If you're not sure, start somewhere, backtest, measure, and iterate. 

This one is going to be simple. Focus on being close to the numbers and be ready to be creative! I do think there are some foundational pieces to building a demand generation engine. The first is having a balanced program mix, make sure are bringing names in a consistent and steady flow. Being close to the numbers helps understanding what channels are working, which channels to invest more time & money in, and making sure these are the programs that convert to meetings and closed won. Once you have that foundational piece, focus on getting creative. At the end of the day, most demand gen teams are running the same types of programs—webinars, emails, etc. It's up to you as the leader of your team to think out of the box. Tip: Look at those programs that are converting well and see how you can hypercharge them by adding a gift card incentive for taking a meeting!

I have some standard 30-60-90 bullets that I apply to any new role. Roughly, those look like this: 30 days - "Listen and Learn" * Complete formal onboarding * Get to know my team/boss/peers * Schedule introduction meetings with cross-functional peers * Understand my job description and key responsibilities * Review current performance data, budgets, and plans * Understand company long-term goals and strategy and how I fit in there 60 days - "Find the Red" * Continue with 30 day items * Dig deeper into metrics, sales performance, customer data, partners * Understand technical workflows and processes * Identify key project areas 90 days - "Build and Change" * Continue with 60 day items * Build formalized plan and socialize with organization * Begin implementing needed changes and working on key projects

Here's a quick laundry list of things to consider without diving into your business model and marketing plans. 1. Partnerships: Do you have partners you can work with to integrate a call-to-action? For example, in one of our small business campaigns where we were targeting small business owners we were able to partner with local banks to include our offering in their small business loan welcome package. I know integrations are tough and it requires more than marketing to champion so I would also think about co-marketing. Are there any partners that have a database of people you are currently not getting in front of? Cross-promoting in partnership channels is a great user acqusition tool. 2. Direct Mail: you're probably thinking this is old school but the campaigns my teams have run are showing positive ROI from direct mail. The reason? It's cheap and you can get a broad reach. We typically pair direct mail pieces with a call to action (ie, register to attend our event, download this ebook, get in touch with sales, etc). This creates a multi-touch journey to your campaigns. 3. Lastly you can run some fun guerilla marketing to drive foot traffic to your storefront. 

Scheduling one-on-ones with your new colleagues is one of the first steps to tackle in your 30/60/90 day plan. In fact, those conversations should influence what makes it into your final draft. You should lean on the team that has seen it firsthand versus thinking you have all the answers. When I first join a company, I make sure that I schedule meetings with at least one representative from sales, customer success, finance, business intelligence, product, and engineering. I also ask these very same questions to every single direct report. Finally, I make sure to interview the longest-tenured employee at the company. 1. What is the best thing that the demand generation team is doing right now? 2. What is something that the demand generation team is not currently doing that you think we should be? 3. Are there any challenges currently facing the organization that the demand generation team should know about? 4. If you had to choose three thought leaders in our industry, who would you choose and why? 5. What are the top three publications/websites in our industry that are frequently read by our target audience? 6. What are the three most common problems customers are trying to solve with our product? 7. What are the three most common objections we face when selling to prospects? 8. Who do you think I should talk to next at this company and why?

* Not necessarily over-hyped, but I think it is important to find the balance between being too focused on top-of-funnel (Traffic, leads, MQLs) and having targets that are out of your control to drive (closed / won, revenue). If your marketing team is ONLY KPI'ed on MQLs and nothing else, you may be incentivized to drive a ton of volume at the detriment to quality. Then your sales team might come back and say that the 'leads' you are sending aren't good quality. If you don't have other metrics further down funnel (I recommend tracking SALs - sales accepted leads, and SQLs - meetings booked or opportunities created), then it becomes hard to identify where you need to optimize and lean in. * I also see a lot of fuzziness around the word 'leads'. In my world today, lead means a net new name to the database. But, I will often hear BDRs talk about leads in terms of the people they are working (so an MQL or SQL), and AEs might talk about leads in terms of the deals they are working (an SQL or SQO). It's really important to make sure you have clear definitions for the KPIs that you are driving and that you are working over time to build a shared language in your organization.

When I think about measurement gone wrong, my first question is typically about the marketer, not the KPI. All KPIs can be useful, assuming your measurement is scalable (i.e., it doesn’t take a week to do the analysis) and you are using them appropriately (i.e., context is everything). That said, here are some metrics that I generally find less material to understanding the health of the business: 1. Impressions/Followers/Engagement: In a world overrun by bots, ad impressions, social media followers, and engagement metrics have become less relevant. You’d be surprised how many companies with massive social media followings built their audiences by purchasing cheap likes from engagement farms. 2. Frontend Email Metrics: Between email preview panes skewing results and well-documented issues stemming from privacy updates introduced in iOS 15, open rates have become far less relevant in recent years and are no longer sufficient to understand if your message is resonating. 3. CPL & Raw Lead Metrics Without Context: Lots of marketers fall into the trap of driving down CPL at the expense of lead quality. There's no faster way to lose the trust of your sales colleagues than flooding them with low-quality leads & expecting them to convert.