Audience targeting is becoming an increasingly sophisticated art through data. Here, we look at three ways you can drive better engagement through different types of data assets and sources.
For the few stragglers who haven’t managed to be swept up in the data revolution, industry research and results point to data-driven marketing being THE way forward for CMOs looking to achieve the ultimate in customer engagement. Getting your marketing team and the rest of the organisation to commit to such an approach, however, can be a challenge, especially when costs, culture shock, creativity and camaraderie between IT and marketing come into it.
To find the way forward, we’ve asked five representatives from various sides of the marketing community – a CMO, analytics leader, data analytics expert, head of one-to-one marketing and a CMO research analyst – to share their tips on how to get your team to rally behind data-driven marketing and your big data potential.
Know your purpose and create an ecosystem
Contributor: Nick Adams, director of one-to-one marketing, Telstra
Good creative instinct can never be replaced, but it will be more informed, structured and based on customer needs and interests thanks to data analytics. I’ve seen an emerging trend that both data and technology are displacing the role creative once played, however it must feed into the process as opposed to replace it. Marketing organisations are now looking to automate the production of their creative effort and directing more investment and resource into technology and data-driven marketing activity, however it should never be an ‘or’ proposition.
The growth in new technologies, amount of data being generated, and the availability of new analysis techniques has created exciting opportunities to provide better products, services and experiences to customers. The key is to explore these while also making sure we honour the trust customers place in organisations to protect their privacy and personal information.
To get your organisation to drive better data analytics, it is vital to ensure your use of big data is in line with the purpose and values of your organisation. The protection of personal information is vital. There are also four elements recommended when entering emerging technology and a big data-led marketing ecosystem:
- Form a technology steering committee: Put together a CMO/CIO technology steering committee, consisting of solution architects, BI and IT representatives. This group needs to meet on a regular basis to build a mutually agreed technology roadmap underpinned with a shared view of the infrastructure required, and the objectives you are trying to reach.
- Appoint an MTO: A new collaborative role, sitting within CMO and funded by IT, the marketing technology officer (MTO) should be an experienced, knowledgeable interface for CMO technology roadmaps and requirements into the IT community. The MTO will not be a PMO, but should oversee the coordination and management of the suite of CMO technology needs.
- Centralised business case management: Business cases for technology should be managed through a centralised function within CMO with highly skilled resource. The centralisation of business case oversight will allow for more robust business cases to be produced and socialised using the appropriate tools and processes into the finance community and capital forums. The centralised business case management team should also have line-of-sight into the organisational funding cycles and will be a central point of liaison and quality control.
- Build technology roadmaps: The MTO and technology steering committee need to build out a set of technology roadmaps with a three-year horizon. The roadmap should identify the target architecture, the rollout schedule and capital profile. It is critical that change management is accounted for and funded and that there is a clear understanding of the hardware and software requirements. With a shared technology roadmap with the CIO, the selling in to the c-suite is substantially easier.
Make analytics second-nature
Contributor: Michael Pain, Accenture Australia’s Analytics Lead
In Australia, 84 per cent of mid-market businesses have either deployed big data solutions or plan to explore them in the next year. To understand their role in the enterprise today, Accenture recently conducted research among global business leaders to gauge the breakthroughs and barriers encountered by enterprises as they put analytics to work.
The study revealed the use of analytics to aid decisions has increased in recent years, and there has also been a definitive increase in the integration of analytics across the enterprise. One-third of companies surveyed are aggressively using analytics across the entire enterprise and fewer than 10 per cent are not making any use of analytics. Two-thirds had appointed a senior figure such as a ‘chief data officer’ to lead data management and analytics in the 18 months before the survey, and a large majority (71 per cent) expected to do so in the near future.
To compete effectively with analytics, senior leadership, especially the CEO, must also be committed. But most organisations fail to realise that analytical leadership is not just the province of the CEO and the organisation’s top executives; it should be second nature to any manager or individual contributor who seeks to make an impact.
To adopt a company-wide perspective, analysts need to consider whether anyone else in the company will find the same data, technology and analytics useful. Any group in a corporation that shares or could share customers, markets, inventory and suppliers, or any group that participates in the same analytical projects based on those business entities, should be considered part of a single enterprise. It is important for analysts to offer meaningful insights to gain the interest of executive peers.
A company committed to helping its customers and suppliers make better decisions will share not only data, but also analytics and analytical expertise, to create an extended enterprise.
Regardless of which stage of the journey companies find themselves on, big data presents the potential to provide deeper insights into customers and operations, and can ultimately help drive competitive advantage. But the rapidly increasing volume and velocity of structured and unstructured data cannot be easily managed with traditional relational databases and business intelligence tools.
For all organisations, handling the workloads associated with big data will require a robust IT infrastructure with a multi-petabyte capacity and the ability to support up to billions of objects. Because unstructured data represents an increasingly valuable business asset, companies will have to take steps to keep it protected and available. Finally, IT governance will also need to be adapted. As a rule, companies will have to make sure that governance processes are in place for everything from performance management to service chargeback, incident/problem management and service desk support for the big data platform.
In some businesses, big data is mainly deployed to resolve immediate challenges, such as increasing sales, cutting costs and accelerating expansion. As the big data market matures, we recommend companies dedicate some of their analytics activity to initiatives that look beyond current issues and focus on harvesting data sets in a more unstructured fashion.
One way to think about it is locking a creative and an analytics expert in a room and getting them to brainstorm – in an unconstrained manner – ways to combine and analyse data. By synthesising management, marketing, consumer and social media data, what possible analysis could be performed and what new insights could this lead to?
We recommend companies begin by allocating a portion of their big data budgets to conducting more of this wide-ranging analysis. This should range from at least 5 to 30 per cent, and would give analytics professionals the time and resources to ‘play’ in company-wide data sets. As part of this process, companies can also encourage greater interactions between analytics staff and creatives – two groups that have traditionally been quite separate.
At Accenture, we appreciate not all companies are in a position to do this. There are resource-based challenges, and finding the staff and budgets to drive additional analytics activities. On a return ROI basis, there are no guarantees of what may emerge from an open-ended approach. The results may be lucrative or they may be more mundane.
However, in a highly competitive marketplace, this extra analysis may be the key to gaining additional (and sustainable) competitive advantage.
Establish trust through experts
Contributor: Eric Siegel, founder, Predictive Analytics World and author, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
A fear of numbers is well embedded within some of us, and there’s no button to press and instantly transform one to a “quant”. However, with the right experts at hand, not only to drive the math but to explain it, comprehension and trust can be established.
On the trust side, there are ways to deploy predictive models incrementally so that risk is mitigated as much as is desired, thereby circumventing the stalemate that may arrive if an eager and convinced statistician has not gained 100 per cent confidence across 100 per cent of the team.
It's a myth - or misunderstanding - to see a move towards data and quantitative methods to be a move away from creative instinct. The former complements the latter, and the latter is still needed. For example, deciding exactly which customers receive which creative may be data driven, one customer at a time, but the generation of those creatives in the first place still involves purely human creativity.
Big data and creative instinct shouldn’t be mutually exclusive
Contributor: Jonathan Kerr, head of marketing and digital, Auto & General
Big data analytics should be the CMO’s best friend in the boardroom because it is far closer to the language that the CIOs, CFOs and CEOs speak. The CMO should grasp the opportunity to present marketing in that context. It’s relatively easy to discuss the fact that those other roles expect the best in BI and MI to run their operations, so it should be entirely understandable that the marketing department needs to be able to leverage all of its data to grow the business in the most efficient way possible.
Using big data and creative instinct should never be mutually exclusive. In fact they are the ultimate power combination in marketing. A great marketing team should demand the insight provided by data analysis to focus the brief that results in the creative execution, while driving the selection of channel, timing and target audience to generate the most leverage from the creative the team produces.
Work with the CIO
Contributor: Michael Barnes, Vice President and Research Director, Forrester Research
To effectively leverage big data and analytics as a core business strategy, CMOs must start by accepting a basic reality: The only sustainable competitive advantage comes from understanding and effectively engaging with your customers. In other words, in the age of the customer, firms must either become customer obsessed or face possible extinction.
For CMOs and other marketing professionals, this means putting themselves in their customers’ seat and designing marketing activities from a customer-first perspective. But big data remains a problematic term as it is technology-centric and doesn’t appeal to or excite most marketing professionals. At the same time, IT is still focused on retaining ‘control’ of corporate data, despite clear business demand for analytics in areas like new product development, customer segmentation and personalisation. Forrester Research estimates that less than 20 per cent of Australian IT organisations are proactively responding to the clear business mandate to use more types of information, from more sources, to enable timelier, better-informed insights For companies to thrive in the age of the customer, CMOs and CIOs must work together to develop capabilities in several core areas:
- Jointly define and coordinate strategies and approaches for providing information workers with simplified, timely access to customer-related information.
- Define big data initiatives in terms of unleashing the potential value of both internal as well as external, cloud-based data to drive customer insight and activity monitoring. The objective of your big data project should be to enable improved decision-making that quickly impacts product and purchase decisions.
- Never forget that context is key. An effective analytics strategy should also enable the capturing of consumer profile, history, and context and placing relevant messages, products or services in front of them.