When technology is changing fast, strategic agility matters. Find out what it takes to thrive in a data-driven world and the era of real-time action.
The job of a Chief Marketing Officer (CMO) has never been easy. As a key driver of growth and revenue, the CMO defines and maintains the strategy for an organisation’s marketing plan, including pricing, communication, product development, and distribution.
However, being a modern CMO is becoming increasingly dynamic and complex. Over the last decade, the costs of collecting and storing data (big and small) have plummeted. Simultaneously, the digitalisation of marketing communications has resulted in an unprecedented amount of valuable business information. And advancements in computing power and equipment have created endless possibilities to reach and analyse customers. Clearly, the business landscape is transforming fast.
In particular, the growth of specialised advertising, marketing and finance technology (‘ad tech’, ‘mar tech’ and ‘fin tech’) has led to a degree of personalised, one-to-one communication that was not feasible in the past. Customers can now be targeted with the right message, within the right context, at the right time—and nearly everywhere to engage business transactions.
The CMO is held accountable for the business case for using all the technology. Since there is often high pressure to be innovative (or at the very least, to not fall behind market trends), this is a daunting task.
For example, a teenager craving a burger searches her mobile app for fast-food; she’s shown a billboard ad, or a promotion for a nearby restaurant, all the while using her favourite celebrity, colour, or burger to capture her attention.
This concept is called ‘programmatic commerce’, which refers to the use of automation, data and analytics to provide better experiences to customers and increase return on investments. Algorithms and real-time tech platforms do the heavy lifting in the background.
Yet, the rise of novel technologies and targeting options also bears many new challenges for marketing managers. CMOs now face many additional tasks that they need to master. They are expected to evaluate, implement, and maintain customer-facing technology, mobile apps, content management systems, and data-science applications. Moreover, they need to coordinate automated solutions for TV campaigns, social media, display advertising, and email/CRM programs, which are often bundled into a so-called data management platform. Because managing such a ‘tech stack’ on your own is basically impossible, marketing departments typically need to nurture relationships with different agencies and service providers that handle technical interfaces and a smooth integration of data and code.
CMOs need to make expensive but fairly quick decisions as to which systems to use and trust, while coordinating the buying process and implementation with the IT department and legal team.
The fact that more and more platforms and standards are available does not make things easier. This is best illustrated by the development of the technology vendor landscape: in 2014 there were approximately 947 customer technology solutions, in 2015 this had increased to 1876, and by March this year, it had skyrocketed to 3874.
Given the mass of new responsibilities, the pace of change, and the newly required understanding of technology systems and analytics, it’s no surprise that most CMOs feel underprepared to deal with the data explosion (IBM C-suite Study, 2014).
DATA-DRIVEN TRANSFORMATION IS AN ONGOING PROCESS, NOT JUST A QUICK FIX.
THE RESULTING QUESTION IS:
WHAT CAN MARKETERS DO TO NAVIGATE THESE CHALLENGES WELL?
The following tips can help minimize risks and should be considered when extending organisational tech capabilities or selecting vendors and solutions.
Extending organisational tech capabilities
Comprehending structured processes and analytics limitations can often be challenging for marketing practitioners who have, in the past, been guided more by creative thinking.
1.Foster a data-driven culture—from the top, down.
Shifting a corporate culture from an intuition-driven to a data-driven approach may be new to many managers. Therefore, it’s important to send a clear message that everyone needs to back up decision-making with data and empirical findings, no matter where they are in business hierarchy.
2.Educate managers and executives in data science and marketing technology.
Organisations embracing the tech and data paradigm often hire data scientists and PhDs for technical roles at junior levels. Yet, it’s also critical to train senior managers and executives about the possibilities and pitfalls of technology and statistics.
3.Involve IT and legal as early as possible.
Integrating marketing automation hardware and software should be in line with any IT standards and procedures your company and country has in place. This is especially relevant for data privacy purposes. Collecting granular information about customers is helpful for targeted communications, but it is imperative to ensure that no sensitive data are compromised. To avoid any leaks or penalties, IT and legal should be part of the conversation from the very beginning.
4.Accept internal limitations and leverage external resources.
Successful technology implementations and applications require a steep learning curve. Don’t reinvent the wheel and try to buy or license solutions wherever you can. Similarly, don’t hesitate to get help from external specialists when setting up new platforms or data science applications.
5.Take baby steps.
Rolling out new technology and data features takes time. Of course, you can always allocate more engineering resources to any open task, but in reality we are bound either by budgets or the shortage of available talent. This is why it’s crucial to have realistic expectations about timelines of new technology integrations, and take small steps towards becoming tech masters.
TO BE SUCCESSFUL IN THE LONG TERM INTERNAL AND EXTERNAL PARTNERS NEED TO LEARN FROM EACH OTHER AND PULL IN THE SAME DIRECTION.
Selecting technology vendors and solutions
6.Agree on data ownership and insights.
When you start working with third-party data providers or agencies, be clear about who possesses any combined data sets. Ideally, a brand should own any information about their clients and business and be able to access this data at any time.
7.Stay flexible and agile.
Be careful with long-lasting ‘lock-in’ contracts. The field moves fast and a new provider might offer better services. Here it’s also vital to consider how agnostic possible platform partners are. Can you freely choose and exchange different pieces (analytics, data partners) or are you forced to work with selected vendors?
8.Have a close look at pricing models.
Different stakeholders offer different price structures, such as flat fees, subscriptions, or volume-driven pricing (the latter being very popular in media buying). So while some may seem more enticing—because of smart framing of numbers, such as proving percentages instead of overall costs—it’s always good practice to walk through different cost scenarios and calculate the total costs over a quarter or a year, so that vendors are compared on the same metric. Also consider the economic incentives implied by each pricing model. Could there be a conflict of interest between your objectives, and the vendor’s?
9.Do your homework.
Before signing a contract, check the present client portfolio and testimonials of a vendor. Ask about references. Also, choose someone with appropriate service levels, which is of particular importance if your organisation is not very tech savvy. One helpful indicator is the ratio of sales people to technical support staff. Do they just sell or can they deliver?
Continuous improvements in technology and analytics imply nonstop learning and a willingness to try new things. But isn’t this what makes our roles so exciting and diverse?