With Google now processing over 40,000 search queries every second - a staggering 3.5 billion requests a day – data creation has exceeded imaginable levels. Managed well, this onslaught of information can be used to unlock fresh insights, build better policies and create new sources of economic value. These potential successes, however, depend on companies’ ability to respond to the new challenges associated with digital integration. To remain competitive, organisations – large companies, governments, political parties and associations – need to address the question of how they incorporate this digital tsunami into their value creation process.
Who's taking care of your digital data?
The cyber revolution requires digital integration, not digital acquisition. Yet, many companies still choose to outsource data listening and analytics capabilities and rely on external partners who specialise in gathering online data, to provide weekly or monthly updates about the changing digital landscape. At times, collaborators within the company may get access to dashboards that track on-line content, but usually they lack the time, training and perspective that would allow them to successfully leverage digital data. Of even greater concern, companies don’t even ask themselves where or how they want to create novel value in the first place.
Understanding digital intelligence
The gap between what digital intelligence involves and what brand leaders think it means stems from two major misunderstandings on the very nature of digital data.
The first misunderstanding concerns the rhythm of digital information: this new data is continuous and real-time, from search to geolocalisation to social media and e-commerce data. If we look at companies as social bodies, then digital data represents the new lifeblood that flows outside of them from key stakeholders including consumers, competitors and collaborators. Thus it is vital that companies become more agile in their response to the digital momentum. Corporations’ lack of integration, and their tendency to rely on infrequent updates from outside partners, is at odds with the fluid and ever-changing nature of digital data flow. This does not mean that outsourcing or thorough analyses of stocks of data is bad – in fact these are necessary to understand what’s happening in the long-term or have access to superior analytics capabilities; but the reality is, these companies often lack technical or strategic perspectives to put digital data into perspective.
Smart data rather than big data
The second misunderstanding is that digital intelligence is not so much about quantity but rather about the quality of information. Unfortunately the now popular buzzword “big data” emphasises and overvalues the magnitude of data. Successful digital listening relies less on how much information is heard and more on the quality of one’s listening approach and the extent to which this fits with what the brand aims to achieve.
Brands need to think about the kind of value they aim to create before tuning their listening strategy appropriately. As an analogy, consider a cocktail party and how often it is more useful to direct your ears towards a particular conversation to get meaningful information, as opposed to trying to capture the overall sum of conversations around you. In short, digital intelligence is more about smart data than big data.
This requires brands to be proactive, and not just reactive, regarding the kind of value they aim to create.
3 challenges to successful digital integration
To successfully integrate digital intelligence into their processes, brands need to meet three key challenges: an operational challenge (how to know what to listen to); an organisational challenge (how to share in real time the digital information collected within the organisation); and a strategic challenge (how to systematically use digital insights in the process of creating value).
* The first challenge - operational - seems easy to overcome. To work on it brands need to first think about how to link the desired outcomes (what are the objectives?) with relevant data sources (what type of media platforms or type of data are being accessed?). In some cases, geo-localised data will appear to be of primary importance. In other cases, when focusing on brand perceptions, social media mentions could outweigh other sources. Or, in cases where brands aim to predict whether a trend will garner more interest in the future, relying on search data may be the key.
It is only after these objectives and sources have been identified that organisations should develop an external or internal system to synthesise the insights gathered.
* The second challenge - organisational – involves deciding which parties within the organisation will have access to this data; the terms of their access (such as frequency or training in digital listening); and how the data and insights will be shared within the relevant teams (such as the brand team).
It is at this point that organisations often succumb to the temptation to rely solely on an external provider. However it is now more than ever, that internal input is most vital. Only frequent discussions among company collaborators across different ranks and functions coupled with external intelligence will fully reveal the potential of the data, and yield relevant analyses through the multiplicity of viewpoints and data interpretation.
In service industries such as banking or tourism, giving access to monitoring tools to individual leaders running businesses (e.g. brand managers) is critical to help them track performance on a daily basis and address potential concerns. In fact, a few major brands in hoteling already track their hotels’ e-reputation, make their listening platform available to the hotel’s managers, and include each hotel’s online reputation scores as a part of the staff’s remuneration.
* The third challenge - strategic – involves recognising how each insight brings value to a specific domain of value creation (for instance, identifying whether an insight is particularly useful for the branding strategy or the development of a new product or a staff recruitment policy).
Decision-makers in the C-suite must pay particular attention to how they integrate these insights into their decision-making process. A good example of this is L'Oréal Paris which, having discovered momentum on the web indicating increasing interest for a particular hairstyle in 2011, decided to closely monitor the development of consumers’ interest for this hairstyle. This led to the development of a new hair dye solution targeting this need as well as the integration of their new insights at different points on their value chain, from branding to positioning and to product development. As one example of a more thorough process of bottom-up digital brand building, L'Oréal Paris decided to choose as the brand name for their new product the very term consumers used in their organic searches for the hairstyle (i.e., “ombre”).
Leveraging digital data to create agile companies
In a world where the digital revolution transforms markets and rapidly changes the competitive landscape, the ability to integrate digital intelligence gives companies a significant edge in understanding and anticipating market movements. As the cyber world becomes ever more inundated with information, it is time for brands to integrate digital intelligence into their operational, organisational and strategic decisions, to foster the degree of agility that will give them a sustainable competitive advantage in the decades ahead.
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