Today, marketers are being challenged by the fast-evolving changes driven by digitalisation: a process which has created more channels, opening up new ways 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.

Traditionally, businesses were faced with customer relationships breaking down as expectations changed. However, digital elites, such as Facebook, Uber and Airbnb, are creating innovative business models that deliver a superior experience to customers, providing them with increased control. This transforms customer expectations in terms of how consumers interact with services, the dialogue customers can engage in and the innovative products that they will come across to fulfil their needs.

Now, products and services are a commodity: any industry competitor can replicate a product or service within just six months of launch. This makes the customer experience even more important: it drives loyalty.

As marketers attempt to keep pace with the rate of change, they are moving towards forming meaningful moments, rather than simply pushing product. In local economies, this was straightforward to do as the store manager or assistant had depth of knowledge in terms of their customers. However, as we have moved to global data economies, marketers must use data in an attempt to recreate customer intimacy.

As marketers move towards being ever more data aware, they face some important challenges:

Lead generation & targeting

Today, broad segment-based targeting is recognised as a crude approach to pushing potentially relevant product and service related messaging to customers. This results in customers being bombarded with irrelevant offers to the point that marketing has come to have little to no value. To increase the relevance and likelihood of success of marketing touch points, marketers need to be able to anticipate customer needs and respond to these quickly. To do this, increasingly marketers are 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 key challenge to overcome.

Maintaining a seamless customer experience

Adopting a holistic view of the customer is paramount to being able to monitor, manage and optimise customer experience. To ensure a seamless experience across channels, marketers need to be able to map customer journeys by integrating data. The ability to join this data together and link a customer’s transactions and interactions through a unique customer identifier is essential to decoding a customer’s journey and experience. In addition, multiple marketing functions are moving to owning this end-to-end customer experience, making this task not only desirable but essential. This remains aloof for many companies who have data spread across silos, both internally and externally in the business. This is also not a trivial task as data ecosystems become more complicated with various technologies both on premise and in the cloud. Business silos working in isolation are only able to solve narrow business questions: to have a wider impact, marketing teams must work together across the enterprise to integrate channel, product, customer and marketing data.

Building skills and talent

Recruiting, developing and retaining talent that can assist in working with data is more and more important to organisations as they move to leveraging data in decision making. General understanding of the skillsets required is developing, and it is becoming clear that one individual ‘unicorn’ is impossible to find. Companies must invest in building data and analytics teams that can wrangle and prepare data, analyse datasets, visualise outputs and communicate results to business users, working in tandem to iterate findings. As the number of analysts, data scientists and data engineers grows, companies should also consider how to best structure teams (global versus local to business functions) and how to keep skillsets refreshed. As new tools and technologies continue to develop, team training will be essential to unlocking the full potential of this capability. Analysing data on its own creates insight but does not necessarily create value: it is the implementation of insights and actions that add value. Analytical and data science teams may help marketers to discover new insights. However, traditional marketing teams must also develop a level of data literacy to enable the translation of insights into actions. Data savviness is vital across enterprises, otherwise, data and analytical efforts are being left unutilised.

Increasing ROI

Marketers have consistently struggled to identify the effectiveness of their marketing budget spend. Year-on-year, marketing teams find themselves increasing spend on SEO, display retargeting, referral sites and a myriad of other marketing channels, campaigns and content. Despite this, understanding which content has the greatest return on investment is becoming increasingly challenging. As marketing content interacts with a customer on a journey, each touchpoint has a possible influence on a customer, driving them towards an outcome. To optimise and drive the most out of existing marketing budgets, as well as make a successful argument to increase budget, marketing teams must harness the ability to track and demonstrate tangible ROI.

Identifying real-time capabilities

As the importance of timely interactions increases to ensure a customer receives the right message at the right time, marketing companies must adopt new technologies. Marketers need to capture data fast: tracking customers on their website, on mobile platforms, consuming content, registering online, starting applications and more. Tracking this activity in real time allows recognition of the best time to connect with a customer and interrupt their journey with a relevant message. Identifying and deploying real-time capabilities is a challenge due to the many point solutions on the market today. Integrating these solutions into an existing complex environment takes a lot of coordination, time and effort.


By Yasmeen Ahmad, director of Think Big Analytics, a Teradata company

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