Big Data marketing: how to harness the power of your data?
Big Data in marketing is revolutionizing practices and opening up a whole new world of possibilities for marketing professionals, particularly in terms of improving the customer experience.
At the heart of Big Data lies a phenomenal quantity of data collected and analyzed by companies. How can we harness the power of Big Data, from data collection to data analysis, to optimize our marketing techniques? What data can you use to better target your audiences and positively impact your user experience and customer relations?
Ready to apply Big Data to your strategies and achieve your growth objectives?
Dive into the fascinating world of data and analytics:
Big Data marketing: definition
Big Data, the term used to describe the sheer volume of data generated by the use of new technologies, is becoming increasingly important for businesses. It is becoming a genuine strategic tool, transforming the way modern marketing is approached.
The role of big data in marketing
In a data-driven world, Big Data opens up vast possibilities for strengthening marketing strategy, particularly in terms of customer knowledge. Indeed, its role will be to optimize the user experience, nurture customer relations, and ultimately foster customer engagement.
The company's employees exploit this real-time data to improve marketing communications with their customers and detect business opportunities on the digital medium.
More broadly, companies use this Big Data for analysis and foresight purposes to maintain or create new competitive advantages in their markets.
💡 Having large volumes of data at your disposal won't automatically lead to increased sales or the development of better strategies. While Big Data is an essential raw material for decision-making, its interest lies in the way it is used: the choices made and the actions implemented.
Big Data marketing issues
With the digital transformation of companies, the main problem with Big Data applied to marketing is to extract relevant perceptions and interpretations from the mass of data extracted.
Considering the 4 main principles of Big Data :
ConseilsMarketing
- volume: the company must be able to process and analyze a certain volume of data in order to draw meaningful conclusions;
- velocity: work teams must be able to process information very quickly, even in real time, in order to exploit relevant information;
- variety: marketing must exploit all relevant data sources, then sort and process the most useful information;
- veracity: marketers must use verified information. The effectiveness of actions depends on data quality.
With this in mind, analysis, visualization and reporting tools are essential to give meaning to data.
Benefits: what can Big Data do for marketing?
A winning marketing strategy
Why use Big Data in marketing? Because it's part of an approach that creates measurable added value for the company.
More specifically, in a customer-centric approach - the key to modern marketing - it proves to be an essential building block in the process of personalizing offers and customer relations, in order to develop a definite competitive edge.
In this sense, it provides marketing professionals with numerous benefits. Depending on the information sources used, Big Data can be used to :
- identify major trends,
- the detection of business opportunities and new perspectives,
- understanding customer preferences and behaviors
- predict the timing and channels of sales,
- create tailor-made product and service offers, in line with the issues faced by prospects.
In short, Big Data makes it possible to propose the right offer, at the right time, with the right message, on the right channel, to the right person.
Goodbye spam, hello successful customer experience!
Big Data makes it possible to bypass the acknowledged enemy of marketing: spam. It helps to :
- better understand your marketing targets and their needs,
- capture their attention and arouse their interest in your brand,
- ensure the success of customer acquisition and retention campaigns ,
- increase revenue per customer,
- innovate and support the continuous improvement of your offering,
- reduce attrition rates.
💡 The data collected can also bring to light questions that marketers might not have thought of, and add new depth to the strategies in place.
What data should be collected?
Here are some of the main types of information and digital channels to exploit:
► Technical data:
- search engines: to detect search intentions, the needs expressed by web users, the appearance of strong trends and their evolution over time;
- cookie-type data (browsing behavior): to learn about search information, sites visited and actions taken.
▶︎ Data on user behavior and preferences:
- mobile data (smartphones and tablets): for geolocation, mobile search intentions and user behavior on the web and mobile applications;
- user data: to discover the behavior of web users on social networks, in particular, their personal preferences (pages followed, likes), their engagement actions (comments, shares), their membership of communities, etc... ;
- transactional data: to observe transactions carried out by customers on an e-commerce site (date of purchase, amount, product references, etc.) and obtain indications on basket amounts, purchase frequencies, consumption habits, etc. ;
- data from connected objects (IoT or Internet of Things): home automation devices and voice assistants provide information on habits, tastes, consumption patterns, etc. ;
- advertising agencies: to gain information on web-user behavior, by studying click-through rates, for example.
▶︎ Data from third-party sources :
- open data: open and structured data freely available from public bodies (weather, sites. gouv, etc.) or private companies to obtain information of public interest (environmental, geographical data, etc.);
- statistical data from qualitative or quantitative studies, on consumption habits, equipment rates, etc. They can be carried out independently or at the request of a company;
- data from online forums and recommendation or customer review sites: to gain insight into the issues and concerns of Internet users, perceived brand awareness, consumer trends, and so on.
Faced with this massive amount of data to exploit, it seems increasingly complex to extract value from it in order to achieve marketing success. This requires a cross-channel vision of data, but not only that. How can we achieve this?
How can Big Data be used in digital marketing?
Webtracking and retargeting to optimize the customer journey
✅ Big Data helps to harness information at a very fine level of detail to :
- discover user behavior on all digital channels: you analyze every stage of the typical customer journey at every point of contact;
- expand your knowledge of your target: you gain better insights to build your marketing persona.
👉 The objective? Better target your buyers and provide them with an ever more personalized offer, thanks to a multi-channel and omniscient vision to propose offers tailored to the right target, on the right channel and at the right time, and identify any potential friction points.
Webtracking makes it possible to identify an Internet user's browsing path, thanks to cookies installed on web pages that track their online activity. These cookies represent a set of data such as :
- IP address,
- sites visited
- pages consulted
- actions taken on your site (clicked buttons) or lack of action.
Retargeting offers targeted advertising to visitors who have left your website without taking any action.
🛠️ Webtracking solutions such as GetQuanty are highly effective for exploiting Big Data and running retargeting campaigns.
Marketing automation to automate your processes
Big Data is the ally of automation. Low-value-added processes are automated to increase efficiency and produce value.
You create scenarios of fully automated email sequences to feed contacts with content and messages that help them mature in their purchasing journey, after segmenting your contact base for more effective targeting.
These marketing software applications are interconnected with your CRM to update contact information, perform cross-checking and effectively monitor the customer relationship, from prospect status through to customer loyalty.
🛠️ Marketing automation platforms such as Webmecanik or Plezi enable you to exploit the information collected on your website via forms, in exchange for downloadable white papers, for example.
Predictive marketing to anticipate user behavior
The aim of predictive intelligence is to harness large volumes of data collected from prospects and customers to produce predictions.
This analysis enables us to :
- better understand buyer/user behavior ,
- anticipate their needs,
- sketch out future trends to adapt your strategy and make it more effective.
This contributes to better decision-making, based on factual and statistical elements.
🛠️ The Mapp Intelligence module of the Mapp Cloud marketing solution enables you to collect, analyze and exploit data across a range of channels to extract customer insights. Campaigns can be enriched with precise data, to better anticipate the actions customers will take. Combined with the other modules, it leverages the full wealth of marketing data to become a true omnichannel customer engagement platform.
Data visualization for intelligent data reading
Thanks to artificial intelligence and machine learning, datavisualization makes it possible to make the most of data to better understand it and draw relevant analyses from it:
- study your targets,
- identify your market environment,
- make forecasts, etc.
It provides a clear and relevant reading of essential information, and facilitates the effective management of your actions.
🛠️ A business intelligence solution such as ClicData enables you to aggregate your data from a variety of sources in a single location, display it in the form of visual dashboards and analyze it seamlessly.
Semantic and emotional analysis to understand web users
The concept: scan the web, review platforms and your customer support communication tools to identify positive and negative comments.
🛠️ A solution such as Q°emotion enables you to exploit this Big Data to :
- better understand your customers,
- improve the customer experience,
- manage your e-reputation,
- identify areas for improvement in the purchasing process,
- anticipate consumer reactions and needs,
- better meet their expectations.
Big Data and mega-responsibilities
Faced with the influx of data, as abundant as it is varied, the processing and storage of this data brings with it an essential issue: the protection of personal data, particularly with regard to the RGDP.
Basic principles must be respected in all circumstances, with consideration given to privacy by design in order to build compliant information systems. If companies equip themselves with technologies enabling them to collect, integrate, sort and analyze quality information, they have a responsibility to think and organize their collection systems upstream, so that protection takes place from the beginning to the end of data processing.
Don't hesitate to work with your IT department and your DPO to ensure that data processing is carried out in accordance with the law... and with peace of mind.
What about you? Are you already using Big Data in your marketing strategy? What do you think of the case studies presented in this article?
Updated article, originally published in February 2019.
Article translated from French