I’ve worked, advised, delivered talks or partnered with a growing list of big orgs. Want to add yours to the list?
Here’s an obvious elephant in the room.
Marketing at corporate or enterprise level is largely disconnected from profit-generating activities, because the decisions for marketing are siloed and lack a connection with what actually puts money in the bank.
Most times, digital marketing at enterprise is a branding exercise, keeping up appearances or diluting advertising space being taken up by competitors.
What if every dollar spent on enterprise marketing could be attributed to conversions and revenue?
Well it can, but it requires a fundamental challenge to the way enterprise thinks about marketing. Gone are the spray and pray days, where you could blanket television and radio and call it a day. Those days have been replaced by Facebook Likes and Instagram Follows, and are horribly out of sync with what actually makes money.
In more sophisticated environments, there may even be attribution, connecting an individual from the campaign they were sourced from, and to a landing page action, though unless tracked all the way to the bank, a campaign can be dangerously out of sync with what is keeping the revenue pumping.
Change is required in the way each product vertical and siloed teams at all stages of customer touchpoints make their decisions. Making decisions from data should be pretty much normal in the organisation, the issue is how far does this data span?
If marketing is looking at traffic volumes and landing page conversions as a sign of success, the battle is only one-third won. Individually mapping each customer journey all the way to money in the bank, is key. Only then can you attribute success to a campaign, no matter which team does what and their diverse responsibilities.
Wrangling teams across floors, offices, cities and countries requires a unification of the focal point. We’re all here to make money, though it’s easy to lose focus when you’ve got 10,000’s of employees.
What’s missing is a clear line of sight. Keeping the eye on the prize will provide a true representation of performance at every level of the organisation.
This process is primarily focused around a growth mindset, and a foundation of data unification across the customer lifecycle, and across all organisational customer touchpoints.
So, how can you start to think about, and introduce this kind of thinking into your workplace? Here’s a few things to consider.
What is the growth mindset? If you’re across the inner workings of the tech world, you’ll notice an interesting trend of startups and established tech companies employing growth hackers. A growth hacker is an individual whose task it is to cut through the noise and identify where problems for growth exist, and ‘hack’ their way to solving those problems and improving the bottom line.
Growth hackers are different from marketers, in that marketing is the final component of their process, which is acquiring the customers. As an enterprise, you’re generating plenty of traffic, therefore the challenges are not driving new customers. The focus must be to improve the performance of prospects on their way to, and within the product. Conversions and retention being a core focus, as well as revenue optimisation and churned customer activities.
Top five tips for building a growth mindset:
It’s impossible to do everything yourself, so to execute on growth, you’ll need a diverse team handpicked from your organisation.
The most important aspect you need to have your team operate effectively is freedom. The bureaucracy and ‘enterprise pace’ of things is way too slow for effective growth. This is especially true based on the volume of web traffic your organisation handles, which would allow for you and your team to work at breakneck speed, something most tech companies don’t have until they’re mature.
The perfect enterprise growth team includes:
Fundamentally, making the right decisions about what to improve and how to improve it, requires a baseline of clean data, with end to end visibility of the customer lifecycle. This is no easy feat.
The data you need to begin to understand problems and troubleshoot them span from new customer acquisition and marketing sources, landing pages, in-product tracking, and revenue metrics, which should all be, at the very least, a clear end to end map of how new and existing customers interact with the organisation.
If you manage to pull this off, you’re in a position to go supersonic versus your competitors and capitalise on the market, and potentially even their customers.
When you discover inefficiencies, especially process inefficiencies, you need to put your ‘where will my company be in 50 years’ hat on. Most processes, especially those designed and handled by humans, are inefficient, and could be costing your organisation millions.
Process automation can be introduced at two different levels. Software-powered automation takes a predictable process and ‘productises’ the task, ensuring a data in, data out, task oriented approach can be executed at self-service by a customer, or automatically triggered at a specific event.
Artificial intelligence as an overarching term for machine-led decision making, and can include machine learning, machine vision, neural networks and other applications. The acceleration and advancements in this space creates new opportunities to train and deploy an artificial brain where it’s suitable. Everything from a chatbot client interacting with customers, to risk and fraud detection, and upselling propensity.
Need a hand? This is where the GRONADE team come in.
GRONADE have worked on growth and data projects with enterprise across all industries: banking, finance, insurance, entertainment, gaming, infrastructure, social impact, medical and others, to build a true measure of success, with accountability flowing from customer discovery, through to product and process, and to revenue.
Want in? Hit GRONADE up at access [at] gronade [dot] com.