The future of marketing: Q&A with Andrew Stephen and Yasmeen Ahmad

Recently, Professor Andrew Stephen from Saïd Business School at Oxford University spoke to Yasmeen Ahmad about her thoughts on the future of marketing in an increasingly digitised world, including the key challenges facing marketers today. See the Q&A below:

Stephen: What are the biggest challenges that marketers are facing right now, particularly with respect to how they make use of data?

Yasmeen: Marketers today are being challenged by the fast-evolving changes driven by digitalisation. Today, digitalisation has created more channels, providing additional opportunities for customers and businesses to interact, as well as increased availability of existing and new data-driven products and services. Digitalisation has placed power into the hands of the customer.

As marketers try to keep pace with rate of change, they are moving away from pushing product to creating meaningful moments. In local economies, this was simple to do as the branch manager or store assistant, who had in-depth knowledge of their customer and community. However, as we have moved to global data economies, marketers must use data to try to recreate customer intimacy.

As marketers move to being ever more data aware, they face some key challenges, including:

• Lead Generation & Targeting: broad segment-based targeting is recognised today as a crude approach to pushing customers product and service related messaging that might be relevant. Customers are inundated with irrelevant offers to the point that marketing has come to have little to no value. To increase relevancy and potential success of marketing touchpoints, marketers must be able to anticipate customer needs and respond accordingly. To do this, marketers are increasingly relying on analytical models that can predict customer behaviours through intentions captured in their interactions. Capitalising on granular datasets, such as clickstream and social media, requires access to advanced analytical techniques and tools. Collecting interactions from page visits, clicks, hovers, form entries on a website and translating this into actionable customer insight is a major frontier to be overcome.
• Building Skills and Talent: recruiting, developing and retaining talent that can assist in working with data is increasingly important to businesses as they move to leveraging data in decision making. General understanding of the skillsets required is developing, and it is becoming apparent that an individual ‘unicorn’ is impossible to find. Businesses must invest in building data and analytics teams that are able to wrangle and prepare data, analyse datasets, visualise outputs and communicate results back to business users, working in tandem to iterate findings. As the number of analysts, data scientists and data engineers grow, businesses must also consider how to structure teams (global versus local to business functions) and how to keep their skillsets refreshed. As new tools and technologies continue to evolve, training for teams will be imperative to unlocking the full potential of this capability. Analysing data on its own creates insight but does not create value: it is the implementation of insights and actions that creates value. Analytical and data science teams may help marketers to discover new insights. However, it requires traditional marketing teams to build a level of data literacy to enable the translation of insights into actions. Data savviness is essential across enterprises, otherwise data and analytical efforts are being left behind closed doors.

Stephen: How should marketers effectively blend “the science” of analytics-based, data-driven decision making with “the art” of branding, creative communications, and strategy?

Yasmeen: Traditional marketing often focuses on creating buyer personas, identifying the characteristics of the target customer audience. This is often focused on intuition and research rather than true science. These personas translate to customer segments for broad based marketing campaigns. However, science can play a pivotal role to move marketers from broad based campaigns to targeted messages for specific individuals. Today, we have the science that can detect behaviours, identify hidden needs, profile channel preferences and guide marketers to engage a specific customer at a specific time in a meaningful interaction. Yet, it is still the creative aesthetic, memorable design and carefully thought out copywriting that connects with customers. Science can help us optimise budgets to engage customers to increase loyalty and drive high value behaviors.

As we deploy campaigns and creative to customers, it is art that allows us to tweak the content and improve it over time. However, science also plays a role. Traditional A/B testing can now be scaled to unparalleled levels. Analytics can help us decompose every aspect of a web page, including the shapes, colours, layout, font and more to generate the most appealing interface that increases interaction and the call to action response rates.

Marketers are increasingly understanding that activities must be driven through a blend of art and science. Creativity can guide to a perfect narrative and imagery but it is the data that can forecast demand, driving sales leads, opportunities and, ultimately, value.

Stephen: What does the future hold in the field of marketing and customer analytics? We already are seeing advanced machine learning approaches being used, so what’s next? More artificial intelligence? Something else?

Yasmeen: The hype surrounding Artificial Intelligence (AI), deep learning, machine learning and other analytical techniques has reached a peak in 2017. These techniques have existed for many years but have only recently become relevant. Previously, the technologies needed to utilise AI techniques at scale, on millions of data points, did not exist.

Marketing and customer analytics have used AI and machine learning techniques in the past, but the error rates and accuracy of models was not always perfect. As digitalisation and big data have increased the detail of data and volumes available, machine learning and AI approaches have vastly improved in accuracy and precision. Relying today on algorithms is not only acceptable but algorithms can perform superior to human decision making.

We will see continued uptake of these techniques as businesses gain the skills and toolsets to access AI and machine learning. This uptake will become essential as businesses try to keep up-to-date with data, streaming in real-time. Not only will we see the prevalence of these techniques increase but they will open the doors to automation across the enterprise.

Stephen: What do you see as the biggest opportunities for marketers over the next few years?

Yasmeen: Marketers have tremendous opportunity to become much more relevant in customer journeys, rather than disruptive or intrusive. By delivering messages, offers and services in a timely, relevant fashion, marketers can move from a push to a pull model where customers are invited to engage as they are presented with relevant content that resonates with a need.

With the advancement in granular data collection, analytical techniques such as AI and machine learning, as well as real-time interaction capabilities, marketers will have the perfect scenario to reach the right person with a personal message at the right time. Using data at scale, businesses can bring back the customer intimacy that has been lost as we have grown into global data economies. Moreover, businesses can respond to customer behaviours and needs in real-time.