The paradox: More data does not necessarily mean easier decisions to make
The 2019 edition of PWC’s recurring survey of international decision-makers from major companies revealed a paradoxical situation*: 95% of the decision-makers considered that data is essential to make a marketing decision. But only 15% felt that the data available to them was complete (even fewer than in 2009 – 21%!).
In the meantime, the volume of available data has exponentially grown, driven by the digital transformation.
Increasingly since the 2010’s, journeys, behaviours and conversations leave traces – structured or unstructured like texts or images – that can be collected, stored and processed.
Could this paradox be linked to data illiteracy, i.e. an inability or difficulty in exploiting data?
Why is data illiteracy becoming a vital issue?
Our world has become VUCA (Volatile, Uncertain, Complex, Ambiguous): the current COVID-19 crisis is a perfect example.
Navigating this world is not that easy. But can we imagine navigating in this world without data?
No, for 3 main reasons in our opinion:
- Data is an essential ingredient to nourish a “counter VUCA” (Vision, Understanding, Clarity, Agility) and thus make it possible for brands to adapt to this VUCA environment.
- Data is also a key ingredient to create marketing differentiation, a vital source of value and growth for the brand. Indeed, data can bring:
- Essential knowledge about customers
- The necessary relevance to adapt the offers made to customers
- The transparency demanded by the customer on the brand’s actions to generate trust.
- To be able to optimise the performance of the marketing function (and all other functions of the company), with the help of Artificial Intelligence algorithms.
Data is both a means for companies to adapt to this new situation and to draw from it, the sources for the renewal of their activity.
But how can we take advantage of the opportunities it presents while avoiding the pitfalls and keeping in mind its limits?
How to tame data? A few ideas
Clarify its intention by putting the data at the service of the brand purpose.
A decision is never good in the absolute, it is considered good to the extent that it achieves the objective that the decision-maker has set for him or herself.
Marketing decision-makers must take note of the total change in the relationship that has taken place with customers (and other stakeholders such as employees, associations, etc.) They should not decide “without” taking them into account, the customer is the brand’s most valuable asset.
This posture requires, among other things:
- renouncing the marketing of persuasion (your brand will never speak “loud enough”, and it will cost you too much at the end of the day)
- entering a real conversation (as “markets are conversations”)
- and knowing how to keep it going.
Data makes it possible to get these interactions tracked, in agreement with the customer, beyond data privacy regulations like the General Data Protection Regulation (GDPR) or California Consumer Privacy Act (CCPA) . And become the backbone of the relationship.
Example: Décathlon, one of the global sport retailers, has a clear contract with its clients and prospects. Data is collected to reach brand purpose: to make people love sport.
To avoid the pitfalls of exhaustiveness
The decision to use data to feed brand purpose is helpful to guide daily operations for brand staff. For instance, to decide which data should be collected. Does this data help to reach the purpose? A way to avoid a common pitfall: data deluge.
To open up, get inspired
Many companies have already undertaken a data strategy, some with great success. Why not get inspiration from the best in class like Nike (e.g. consumer knowledge improvement through apps) or Sephora (for instance, enhanced CX delivered in stores through data) . And imagine what their initiatives would mean for your organisation? It should help!
To practise by choosing the first cases wisely
To become more comfortable, the marketing function needs to practice. It can thus intimately understand the strengths, limitations and pitfalls of data for its organisation. The choice of the first use case is pivotal. It must allow a real painful point to be addressed in a qualitative way, within a reasonable time and at an acceptable cost.
To acquire skills and to ensure autonomy on strategic issues
This can be done through staff training and this should be fostered. New employees could be recruited to fill the “skill gaps” while making them collaborate with current employees: everyone learns from each other. The use of external service providers is likely to be necessary. In this case, make sure that the internal teams are able to keep control of the projects.
To define the roles between the human and Artificial Intelligence
With the development of different forms of AI (for analysing quantitative data, text data or images) to cope with data flow, a concern may arise among employees: the loss of one’s job. Marketing staff, with Augmented Intelligence, must concentrate on what the machine will not be able to provide: creativity, the meaning given to actions, the link created with customers, etc.
A purely mechanical approach is orthogonal to todays customers ’expectations.
Conclusion
Clarifying one’s intention on the use of data is the first essential step. The use of data is not a step to be taken but a road to be travelled. Change management and soft skills development will be much more important than technology.
* https://www.pwc.com/gx/en/ceo-survey/2019/report/pwc-22nd-annual-global-ceo-survey.pdf p29
