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There’s one topic that never fails to get people talking at our events: Marketing.
And this year was no exception.
The TL;DR? There’s a shift happening. Away from a marketing function that focuses on creating awareness, generates pipeline and throws MQLs to the sales function to one that directly drives SaaS revenue too.
During her fireside chat at SaaStock Europe, Gong CMO Emily He explained why aligning marketing with revenue is the prevailing SaaS marketing trend and how AI can unite the whole go-to-market function into one ‘revenue team’. In particular, she called on SaaS CMOs to better understand marketing’s impact on revenue along the customer journey and to leverage AI to make that happen.
Watch the full session below or read on for key takeaways.
Aligning marketing with revenue
1. Work towards common goals
Marketing and sales used to collaborate like a relay race: marketing ran its process and passed the baton over to sales. But now marketing should be active throughout the entire funnel, so having common goals is vital to ensuring a streamlined approach.
‘Work with product, customer success and the sales team to come up with a common set of KPIs and metrics. Then hold all the teams accountable for the entire funnel and the revenue impact.’
2. Use full funnel metrics
SaaS marketers tend to use awareness metrics to gauge its impact on the pipeline at different stages of the funnel, be it through events, digital programmes or how customers consume the website. But now you need to come up with full funnel metrics for all GTM functions.
‘Metrics are more around the impact on revenue and cost of customer acquisition versus the traditional pipeline metrics. Really identify the right metrics and KPIs that everybody is accountable for and have a lot more real-time conversations to measure whether you’re moving in the right direction and achieving these common goals.’
3. Focus marketing on revenue impact
With sales and marketing working together across the entire funnel, the focus shifts to customer acquisition and the revenue impact. By using AI insights, you can focus marketing efforts on what generates the most revenue (not the most leads) and iterate constantly.
‘Account-based marketing used to be reserved only for large enterprise accounts, but now you can do that for almost every single account. With full visibility of how customers have interacted with you for every account, you can inform your further interactions with the customer and accelerate revenue generation.’
Using AI to align marketing and revenue
1. Capture the right customer data
Gone are the days of trying to infer customer intent from data; with AI you can really see what customers are thinking. AI tools not only learn what’s actually happening with customer accounts and identify common trends, but can turn this data into tangible revenue insights, such as churn risks or customer requirements (which marketers can translate into messaging or marketing programs).
‘To truly take advantage of AI you need to capture the right data and train AI to tune into the needs of the revenue team. Gong, for example, captures conversation data, so you hear directly from the customer regarding their technology requirements, business priorities, competitive concerns, and questions about pricing and packaging. This enables marketers to truly be that voice of the customer, instead of a salesperson’s inputs into the CRM.’
2. Customise your approach for every customer
From marketing techniques to sales messaging, AI gives you a more in-depth view on what is and isn’t working with specific customers. By collaborating with the entire revenue team, you can pivot the whole GTM approach in real-time (i.e. for individual accounts or personas) and make changes to who you’re selling to, how you’re speaking to them, and at what price point.
‘If you have the right data, AI can go through the interactions the customers had with the account, and it can marry that with the right product information, the latest and greatest pricing and packaging, and surface the right recommendations as next steps for the customer.’
3. Focus AI where it’s more proficient than humans
AI doesn’t do everything well. For instance, creating a brand strategy or product messaging requires too much cross-functional knowledge and out-the-box thinking (e.g. referencing pop culture), while AI also struggles to foster deep connections with customers. But there are some areas where AI is more proficient than humans. For Emily, that’s personalised customer engagement (highlighted above), as well as lead scoring and content generation.
Lead scoring – ‘If you feed the right historical data to AI, you can sort of tell AI what’s right and what’s not, and train AI to watch for the right signals and take that into account in lead scoring.’
Content generation – ‘Not strategic content generation, but if you want AI to write a social post or a piece of collateral, AI is getting pretty good at it if you feed it the right data.’
The future of the marketing tech stack?
Be it in sales, marketing or customer success, SaaS applications have historically been designed for particular personas and workflows. But going forward, SaaS applications will likely support all go-to-market departments with AI data insights solving workflow pain points.
‘In this new era of AI, with data being the foundation, there’s going to be a whole class of AI-first, data-first applications. By turning data insights into applications that support the workflow, it’s kind of the reverse of how we build applications today.’
By merging tons of insightful customer and engagement data from across the aligned GTM and revenue function, SaaS companies will have a better understanding of what customers actually want and be able to produce a consistent product, marketing and sales experience. Or, what Emily calls, ‘Nirvana.’
