Every minute, 48 hours of video are uploaded to YouTube, 204 million emails are sent, 600 new websites are created, 600,000 pieces of content are shared on Facebook, over 100,000 tweets are posted and over 2.4 million queries are made on Google.
It is becoming increasingly difficult to extract meaning and useful information by following the traditional process: acquisition, storage, processing and analysis over several days, weeks or months. Smart Data is the answer to this problem.
What is Smart Data?
Smart Data is the strategic use of relevant, high-quality marketing data to meet a company's specific needs. Unlike Big Data, which accumulates large quantities of diversely structured data, Smart Data prioritizes quality over quantity. It involves collecting, processing and analyzing data in such a way that it can be immediately exploited for rapid, effective decision-making. This includes filtering data to retain only that which is essential and useful for optimizing marketing strategies and improving customer interaction.
For once, we're going to offer you a patchwork of definitions to help you grasp this concept, which is still (somewhat) in search of its identity. Just take a quick look at the web for proof.TechTarget, FedTech, Wired and IDG all offer different but (broadly) complementary conceptions. Compilation:
For NetScout, it's " customer data that has been prepared and organized so that it's ready and optimized for fast, high-quality analysis ".
For FedTech, it's digital data that's independent of any software, application, peripheral or network, but which is nonetheless exploitable. It stands on its own, but can always be integrated into a larger whole. " This customer data is imbued with context, and this context is added as close as possible to the source of acquisition .
FedTech's view collides with that of Wired, for whom Smart Data is the result of the analysis of raw digital data by intelligent algorithms. In short, the tech magazine equates Smart Data with information produced from raw customer data... with the nuance that this processing must be carried out rapidly, even in real time, to fuel decision-making before marketing data becomes obsolete.
TechTarget believes it's primarily a question of timing. " It's digital information that has been properly formatted from the point of collection, before it goes to the analytics platform for further processing ."
For its part, Creamfinance contrasts Big Data and Smart Data head-on. " Big Data refers to the misshapen mass of marketing data that floods companies on a daily basis. Smart Data, on the other hand, is a collection of relevant data that speeds up information processing .
If we put the pieces of the puzzle together, ignoring contradictory points, we can define Smart Data as a set of customer data streamlined around the point of collection:
Before : identifying the data you need to make decisions
During : ensure that data input is monitored by a real-time validation system, according to pre-defined compliance conditions
Immediately afterwards: Extract a first batch of information from the data in real time, facilitate further data processing and reduce the time between acquisition and data extraction to support decision-making.
Smart Data: what's at stake?
Data volumes are already posing organizational and technological problems for companies, even those with dedicated data marketing teams. And the trend is set to continue, with exponential growth fueled not only by the digitalization of behaviors, but also by "demographic" growth.
When exhaustiveness becomes complicated, or even impossible, it will be a matter of injecting "intelligence" into the process, by taming the volume upstream, and then at the point of collection. The stakes are enormous:
As we explained in this article, 65% of B2B companies are expected to complete their transition from a flair- and intuition-based decision-making model to a fully Data-Driven marketing strategy by 2026, according to Gartner. Structures that have not built an effective framework for operationalizing Data by 2024 will lag behind in competitiveness by at least two years.
According to Nielsen, access to analytics is "extremely difficult" for 36% of marketers
According to Gartner, 57% of salespeople and 51% of marketers have to contend with data skills that are well below average.
Intelligently acquired data could remove a great deal of friction, and facilitate its rapid and relevant integration into the decision-making process.
4 crucial strategies for migrating to Smart Data
Determine which data is (really) useful for the decision-making process. In short, it's a question of adapting the size of the mesh to your needs (and your analytical capabilities): too tight a mesh will result in a deluge of raw data that's very expensive to process, and too wide a mesh will result in incomplete data that's difficult to contextualize.
For data to be Smart, it must first be "clean". Poor-quality data costs companies 12% of their revenues (Experian). Garbage In, Garbage Out! Data Enso has developed simple, 100% RGPD-compliant solutions to ensure the quality of your data both preventively and curatively.
Rework your organization to decentralize data analysis. With Smart Data, value begins to accumulate soon after acquisition. Teams can therefore act more quickly, without necessarily having to resort to advanced analytics.
Adjust your technological stack to take advantage of Smart Data over the long term. Your tools must enable non-technical teams (Sales and Marketing) to extract a first layer of information from Data as soon as it is acquired. They must also be scalable to adapt to the growing volume of Data to be collected.
