Growth Marketing on an enterprise scale: Part 1– 3 Challenges

Growth marketing is an intersection of Data Science, Marketing and Product Management

Growth marketing today is a bit like Product Management used to be 10 years ago — a rapidly growing and often misunderstood function that’s highly variable across organizations. It’s also a unique skill set that’s in rather short supply — equal parts Data Science, Marketing and Product Management. Yet, we’ve come a long way since the time Facebook pioneered the practice to grow its ~50M MAUs to 1B+. There’s some amazing blogs, podcasts and even a dedicated conference about the practice (some of which are listed at the end of this post). LinkedIn pegs the no. of Growth Marketing jobs at 7.5K+ in the United States, vs. 25K+ for Product Marketing and 115K+ Product Management jobs. That’s pretty amazing growth for a function that’s relatively new in terms of being an official job title.

However, the more you dig into it, the more you’d observe the examples, best practices and thought leadership to be focused on companies or platforms with small to medium scale — from Stage B to just over post-IPO scale. (Note: Growth marketing is most effective when a product finds product-market fit, adoption reaches a critical mass and churn has stabilized to manageable levels. So you don’t see a lot of examples at very early stages in the maturation cycle). So what about enterprise companies such as the FAANGs, Microsoft and others? As a growth marketer at Microsoft, I constantly grapple with problems similar in nature to the ones growth marketers in the valley are trying to solve. However, I constantly learn the hard way that the same solutions are not effective at enterprise scale, irrespective of how much product innovation your company may be driving.

I’ve learnt that there are three main challenges that make Growth Marketing less likely to be effective in an enterprise. Carefully auditing and removing bottlenecks in these areas in your organization could position your growth team for success much better. Some of these may seem obvious, but their impact on growth activities is more magnified than on day-to-day product and marketing activities.

Functional silos

Product and marketing teams in a software company spend most of their time doing two primary activities, respectively —(a) building a product people love and (b) growing adoption and/or sales efficiently and with the ability to scale. In companies where product and marketing are part of separate units (such is the case with Microsoft, Google, Amazon, etc.), efforts across these two key activities often become parallel workstreams, instead of being two levers of a single workstream. This causes each function to run growth experiments with the levers available only to them, even if they may not be the most effective levers at driving a certain outcome. For instance, marketing teams at Microsoft routinely set up emails for user onboarding and engagement. But often these emails are not accompanies by a solid onboarding experience in the product, leading to a high churn rate (emails are out of context and not always the best onboarding mechanism if delivered standalone). On the other hand, engineering teams that track churn as a KPI routinely try to do in-product optimizations to improve churn, even though the most effective tactic here could be a proactive email sent to a user who may never return to the product again, but may still read the email.

Obviously, placing a growth team in a specific functional unit would not be effective.

How do you create a growth team that’s more cross-functional?

Data silos

The reason why growth marketing at Facebook is so effective is that they have a consistent user id (a 128-bit UUID) across all products such as news feed, photos, etc. Designing your data schema around this single unit of identity is often a far-fetched dream for enterprises like Microsoft, that are moving from desktop software to cloud software, devices, etc. Further, if the company happens to be in the B2B space, a user is not always a well defined entity — often several separate users may come to visit your website, a different user may decide to purchase your software, yet another user may actually buy and administer it, and a completely different set of users might end up using it. Various commerce engines and marketplaces, GDPR protections and a plethora of other issues make the story far more complex here than for a SaaS company.

Who is your end user? Getting to an identifiable user is incredibly hard! Even if you do — all the best trying to work with managing opt-in/opt-out.

Inevitably, a large company will drive some standardization of its data infrastructure across its product, marketing and sales teams with the best intentions. For instance, a lot of large companies are choosing to dump all of their product telemetry, commerce and user PII data into a data lake. Now, what if a team wanted to use a combination of this data to create an email campaign? This is incredibly hard with existing tools for running email campaigns (Intercom, MailChimp, Exact Target and others). Most email tools like data to be stored in structured SQL databases. Marketers also do not have the skill set to query data lakes directly to build their campaigns. Finally, if you do use a third party tool, you’ll have to find a way to sync user’s opt-out of promotional emails back with your company’s permissions master database. Phew!

How do you work with this clunky infrastructure? You can kiss agility goodbye!

Inability to use the right tools for the job

Data silos is not the only issue that comes in the way of using the right tool for the right job. Big enterprises are more wary of user data when it comes to using it to offer personalized or tailored experiences — which is a key tactic for growth. This wariness is even more pronounced now under the GDPR regulations. For instance, Microsoft’s Privacy and Cookies terms commit to not using cookies for re-targeting users with display ads on ad networks. This hurts any team that’s looking to do demand generation or drive engagement for existing users, since re-targeting could be a very effective technique for both scenarios.

Data governance and protection issues also often act as a barrier to teams adopting best of breed tools. Just buying a subscription for Intercom was a 1.5 year journey for us, because we had to cross several privacy, accessibility and legal validation checkpoints for scenarios in which Intercom was going to have access to our user data and telemetry. A growth team would also need tools such as Google Analytics, Optimizely for A/B testing, Usabilla for user feedback, Segment to combine data from disparate sources and others across the user funnel. Because all of these tools need data to be stored outside the company’s firewalls, using them is rarely a trivial decision point.

How do you get around the inability to use promising tools and still iterate on growth experiments?

The final picture

What you ultimately end up is a world where several teams are reaching out to the same user through their own channels, but unaware of the other channels that may be trying to drive to the same outcome. With luck, you could have a constructive effect of these efforts. But most often it results in the user getting spammed with disparate messages. If we try to depict this in a more visual way, you end up with something like below.

The messy world of growth in an enterprise company with a portfolio of products

My intention with this series of posts is to highlight how growth marketing in enterprise companies needs some more key ingredients than growth marketing in newer, smaller companies. However, by no means does that mean that growth marketing is not your cup of tea if you’re an enterprise and B2B marketer. With creative organizational alignment and growth tactics that borrow from industry leanings but adapt them to your organization’s unique challenges, you can accomplish a solid ROI from your growth efforts.

Meanwhile, I’d love to hear your growth challenges. How do you think about growth in your org and what prevents you from being successful? Have you learnt creative tricks to get around these roadblocks? Please leave a comment!

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Ayush Jain is a problem solver first, and a Marketer or Product manager second. By starting from the user and understanding the most effective lever to solve a problem, he works across product and market levers on growth projects that create value for users and move them along in their journey with the product. He currently works on growth for Microsoft Azure.