Customer experience management is a team sport. Just like Cristiano Ronaldo or Messi cannot single-handedly win the world cup for their country, it is the same case in customer experience management. The customer facing team are the forwards, the data science folks are the solid middle where the next attack takes shape, and the defence is the Martech and IT support which is the backbone on which the whole winning edifice is built. If the middle comes off, everything is disjointed, the customer journeys and experiences are likewise broken.
Data science and customer experience looks divergent to start with, but it is this combination of the left brain and the right brain that will drive sustainable business growth through delivering relevant and meaningful customer experience. Each team is dependent on the other to fill in their knowledge and skill gaps.
Marketing data is the most unexploited organisational asset. There are three data sets that an organisation potentially has:
- Hard Data: This is the transaction or purchase and service history data.
- Dark Data: This is the data collected in the process of selling or providing the service but not effectively captured. It lies somewhere in the organisation, but the marketing decision-makers are unaware of its presence or do not know how to use it or it is so badly structured that it cannot be used.
- New Or Soft Data: This is typically about the behaviour, activity, or interest of the customer. At another level, it is all about capturing the ‘intent’ of the prospect or the customer from the trail of information that the customer is leaving behind in the digital ecosystem. Insights can also come from new sources of data. For example, for Health and Life insurers using emerging categories of data sources from fitness bands enables them to understand customer lifestyles better and recommend plans and pricing in that context. Car insurers can use data from a variety of IoT devices fitted in vehicles, they can then recommend plans based on this data.
Some of the key data sets that a Marketer would be interested in to help him make better informed decisions are customer, service, financial, and operational data.
- Customer, Transaction And Service Data: Name, email, mobile, address, transaction and/or purchase history and service history. This will include all kinds of digital behaviour data like web searches, time spent on products and services, which pages were the most engaging, channel preference, CRM and Loyalty programs, Referral data, Call centre data, etc. Also, if analytics is deployed then – CLTV, Market Mix Modelling, MROI and other analytics models can be built, including next best offering, churn, etc. Very few organisations incorporate or use qualitative research in conjunction with other data points that they have. The organizations’ ability to integrate behavioural insights with intent insights and transaction insights will drive a competitive edge in the future. Qualitative insights can also come from surveys, social media, and online communities. Combining marketing and sales data can bring a holistic consumer view. This will help identify the gaps and enable teams to devise the right interventions for both the sales and marketing teams.
- Sales And Financial Data: Understanding the sales data granularly will help marketers develop sharper strategies based on cultural traits, regional behaviour, language nuances, social habits, or specific product preferences. It helps them measure performance and operate more efficiently. Understanding Sales and Marketing costs including margins and competitors’ financial data (if accessible) are other important data points that marketers need to be on top of to drive financially viable and optimised budgets.
- Operational Data: This is connected to business operations and processes. For example, for automotive players, shipment of cars, availability of models, dealer network and its efficacy and effectiveness, sales, and network support. All of this can aid effective formulation and deployment of data driven marketing strategies.
The primary benefits of data driven customer experiences are:
- Gain 360-degree customer insights and better business intelligence across departments,
- Identifying opportunities for growth by spotting trends and patterns and connecting them to customer touchpoints,
- Meeting customer needs that they may not have expressed directly, build new behaviour driven models, next best offering, churn analytics,
- Help map out the customer journey to identify issues, drive efficiencies through channel optimisation and cost savings, and
- Determine the ROI of marketing initiatives using data.
Marketers are slowly moving intuitive customer experience to data and intelligence driven customer experience to score goals with their customers and have begun organising their teams for the CX driven world cup.
