AMA: Atlassian Head of Lifecycle Marketing, Portfolio, Ashley Faus on Product Marketing / Demand Gen Alignment

This varies widely by company, org structure, and maturity. When I worked for smaller start-ups, we only had 2 dedicated marketers: me (generalist) and my VP (also a generalist, but she was running sales as well!). In that case, I had to divide my time by priorities for the business. This was determined as part of quarterly planning and product launches. If we had a product launch, then that quarter was dedicated to building the materials for the launch, and promoting the new product. In quarters where we didn't have a launch, I split my time among the other activities, based on the data. What are the top 2-3 goals your company wants to achieve, and on which time horizon? If they want to acquire new customers, demand-gen and sales enablement would be your top activities. If they want to drive Monthly Active Users and feature adoption, more traditional product marketing activities would be a better focus. In larger companies, there is a dedicated team for each of these areas, though they should be coordinating and collaborating. For example, at Atlassian, we have separate PMM, Demand-gen/CLM, and Sales teams. We also have a Customer Success team who helps with the retention metrics. And "retention" might include cross-sell, up-sell, and expansion, which is a mix between PMM, CLM, and Growth teams. There's many levers for each of these activities, so dividing them up based on skills and capacity is key. Some organizations focus their demand-gen teams exclusively on getting new customers into the pipeline. Some organizations want their PMMs to do lots of sales enablement, while others have them focus on collaborating with Product and influencing the roadmap. I would argue that Sales should not fall into the marketing roles you mention, as that's a different skill and different activities. Sales should be focused on closing deals, which is a short-term metric. Marketing requires balancing short- and long-term metrics, so the strategies, activities, and skills are not the same as Sales.

We have a dedicated ABM team, but they partner with the Product Marketing team when they need specific proof-points related to a persona, vertical, or pain-point within an account. They create personalized landing pages, host curated events like roundtables, and go on-site for larger customers. They have much more niche segmentation for their digital campaigns. In contrast, traditional marketing is more scalable and created for a bigger target audience. Our Product Marketing and Customer Lifecycle Marketing teams run these scalable campaigns and programs, while the ABM team handles the tailored experiences. As an example from a former company, we worked with a large customer who had specific requirements and tiers for someone to be a spokesperson on behalf of the company. They were strict about which employees were allowed to speak publicly for or about the company, and moving up into a new tier was an important part of growing your career there, particularly at more senior levels. So, we created some customer criteria and trainings to match employees who were looking to move into the next tier. It was more than the standard messages around persuasive presentations, having influence, and getting your message out to the world. It specifically used the language that these employees heard internally about skills and abilities to move up.

Depending on the size of the launch, we have multiple teams involved, not just Product Marketing and Demand-Gen. I'll also note that Product Marketing and Demand-Gen teams SHOULD be working closely together, all the time. Both teams should be contributing to the short- and long-term success of product sales, and a launch is just one moment in time. For example, for a Tier 1 launch, which means that it's an important launch, receiving lots of marketing support, we break down the following: For up to 30 days post-launch: * Social Media mentions and sentiment * Press coverage, including number and nature of outlets, message pull-through, and sentiment * Entrances to the product or feature landing page * Sign-ups (if it's a new product) or feature usage (if it's a new feature in an existing product) * Email open-rates and click-through rates for the announcement and/or content related to the product * Views and average watch time of the announcement video and associated demo videos Most of those metrics are driven by product marketing and the communications team. We do measure sign-ups and feature utilization long-term, but those metrics wouldn't be attributed specifically to a specific launch. Product marketing is generally responsible for delivering the messaging and sales enablement materials, as well as key asset related to the product (demo video, product tour updates, screenshots of the product for social media, etc.). Demand-gen teams usually run longer-term campaigns, and might use the new product launch or feature release as part of a larger campaign. If the launch is big enough to warrant a full campaign, the demand-gen team and performance marketing teams would partner to own metrics like: * Impressions and clicks from paid ads * Entrances and conversions on the campaign landing page * Cost-per-click, cost-per-view, and cost-per-lead * Contacts and/or leads from the campaign * In-product message conversion rates * Webinar registrations and replays/views of content related to the announcement or follow-on product content The demand-gen team generally manages contracts and placements with paid partners (in tandem with the performance marketing teams, each own different vendor relationships), reporting, orchestration for distribution channels. All of these metrics would be reported to leadership as metrics of success of the launch, and early indicators of customer satisfaction and adoption of the new product or feature.

This answer differs, depending on the size and structure of the organization. However, there's some common themes, including: - Product Marketing should be the experts in the product, audiences, and messaging. They should be able to articulate WHO we should be talking to, and WHAT we should be talking about that will resonate with those people. - Demand-gen and growth teams should be experts in reaching relevant audiences. This means that they know WHERE we should be talking, and HOW to talk in each channel. - PMM and Demand-gen work together to match the right messages for the right people in the right place at the right time. Practically, this means that Product Marketing provides message houses and audience insights to the Demand-gen team, and the Demand-gen team recommends the channel strategy and asset mix. In many organizations, there's a content strategy team that helps to create assets and gives recommendations on which assets are best for each channel. They advise PMM on which messages work well in different formats, and advise Demand-gen on which formats work well in different channels. This team also collaborates with teams like SEO/Editorial, Events, Email, Ops, etc. to expand the channel mix beyond traditional paid channels associated with Demand-gen responsibilities. The key to making this work is tight collaboration between the teams, with a high level of trust. This is not a "throw it over the wall" scenario, where PMM does a one-time hand-off of a static message house, or Demand-gen simply shares monthly or quarterly reports about campaign performance. Both teams need to have regular syncs, exchange information about what's working and what's not, and work together to fill any gaps in the audience journey.

The biggest key is alignment on priorities and goals. We can't run a campaign for every single feature update or asset, particularly if we have a large portfolio of products. So, we need to know which product(s) are the priority for each quarter, half, or year. And we need to know which goals are most important for those products. If we're announcing a brand new product, awareness might be the biggest goal, and we might have a larger budget to put into paid media, since we're trying to drive a net-new conversation. If we're facing headwinds from a specific competitor, we might need to focus more on enabling the sales team to handle objections or be strategic in our conversation with key accounts. Retention and expansion might be more important in this case. Next, quarterly planning rituals are key. The teams need to be talking to each other, meeting regularly, and aligned on which narratives are driving the goals for each quarter. We use Confluence templates for this, including these: https://www.atlassian.com/software/confluence/templates/project-plan https://www.atlassian.com/software/confluence/templates/marketing-campaign https://www.atlassian.com/software/confluence/templates/marketing-plan Finally, Product Marketing teams should keep message houses and persona information up-to-date to inform Demand-Gen deliverables. These are key to helping the demand-gen team know who to target and which messages resonate with each audience.

For folks who are unfamiliar, here's a short note on some key elements of the Content Playground framework: - The traditional funnel struggles to capture the full buyer's journey, since it only starts when the marketing team recognizes that someone is on a journey. Most people are NOT in the market to buy, and they do a lot of their research before they raise their hand to show that they're buying. - Thus, we need to stop mapping content to the traditional phases (awareness, consideration, and decision), and instead, map them to content depths (conceptual, strategic, and tactical). Conceptual is the "what" and the "why" of the idea, and helps the audience understand the problem space. Strategic is the tools, processes, and key knowledge components that must be in place to make the conceptual ideas reality; it helps the audience think about the solution space, and equips them to do their own research. The tactical depth is the prescriptive, step-by-step instructions and ongoing habits to implement the idea. - We must also look at multiple intents, not just buy-intent (the traditional funnel assumes that all content is ultimately buy-intent). But the Playground means we recognize that there's also use-intent, help-intent, trust-intent, and learn-intent. As we think about this from a marketing and content creation perspective, we need to think about the next action and explicit CTAs. For example, if the next action is to log into the product to do something, the content is use-intent content. If the next action is to contact sales or sign up for an account, then it's buy-intent. True learn-intent content doesn't require the audience to do anything "beneficial" for the company. They might tell their team about the idea, think about it while they take a while, or share it on social media, but they're not necessarily doing something that we can "track" as part of the "funnel". When it comes to AI, I think that the initial content mapping needs to be done by a human, because it's a mix of art and science. Figuring out which narratives to focus on, how to frame them, which depths are most important and which narratives have enough depth to fuel programs and campaigns is the strategic and creative work that humans are good at and enjoy. However, getting audience insights can be a use case for incorporating AI into the workflow. For example, using it to summarize customer research or user interviews, helping to pull out patterns to inform the content mapping process. It can also be good for helping you understand the language of the audience and topics the audience is most interested in hearing about. For example, it can help you identify the most-asked questions if you give it a bunch of webinar transcripts. It can also help you see most-used words in customer conversations to help you mirror the language of your audience. Because the Playground is about seamless hand-offs and allowing your audience to choose their own path, it requires a lot of content. AI can accelerate repurposing efforts. For example, we've been experimenting with AI-assisted clip creation, using a tool to help generate short clips from a long-form video. We've also used machine-generated transcripts to make it easier to create long-form or short-form written assets from podcasts or webinars. These are basic use cases that go much faster as the tools get smarter.