Big Data marketing: how can you harness the power of your data?
Big Data in marketing is revolutionising 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 amount of data collected and analysed by companies. How can you harness all the power of Big Data, from data collection to data analysis, to optimise your marketing techniques? What data can you use to better target your audiences and have a positive impact on the 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, in particular by transforming the modern marketing approach in depth.
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. Its role will be to optimise the user experience, nurture customer relationships and, ultimately, foster customer engagement.
Company employees use this data in real time to improve marketing communications with their customers and identify business opportunities in digital media.
More broadly, companies use this Big Data for analysis and foresight purposes to maintain or create new competitive advantages in their market.
💡 Having access to large volumes of data will not automatically lead to an increase in sales or the development of better strategies. While Big Data is an essential raw material for decision-making, its value lies in the way it is used: the choices made and the actions implemented.
Big Data marketing issues
With the digital transformation of businesses, 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 analyse a certain volume of data in order to draw meaningful conclusions;
- Speed: work teams need to be able to process information very quickly, even in real time, in order to make the most of 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 the quality of the data.
With this in mind, analysis, visualisation and reporting tools are essential to give meaning to the 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, as part of a customer-centric approach - the key to modern marketing - it is proving to be an essential building block in the process of personalising offers and customer relations, in order to develop a clear competitive advantage.
In this sense, it offers marketing professionals numerous benefits. Depending on the sources of information used, Big Data can be used to :
- identify major trends
- the detection of business opportunities and new perspectives,
- understanding customer preferences and behaviour
- predicting the right time and channels for sales,
- create tailor-made product and service offerings that address the issues faced by prospective customers.
In short, Big Data makes it possible to deliver the right offer, at the right time, with the right message, via the right channel, to the right person.
Goodbye spam, hello successful customer experience!
Big Data makes it possible to get round the acknowledged enemy of marketing: spam. It helps you 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 the revenue generated per customer,
- innovate and support the continuous improvement of your offering,
- reduce the attrition rate.
💡 The data collected can also bring to light questions that marketers might not have thought of, and add new depth to the strategies put 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 emergence of strong trends and their evolution over time ;
- Cookie-type data (browsing behaviour): to find out search information, the sites visited and the actions taken.
▶︎ Data on user behaviour and preferences:
- mobile data (smartphones and tablets): to find out about geolocation, mobile search intentions and user behaviour on the web and mobile applications;
- user data: to discover the behaviour of internet 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 to obtain information on basket amounts, frequency of purchases, consumer 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 the behaviour of web users, 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 data, geographical data, etc.);
- statistical data from qualitative or quantitative studies, on consumer habits, equipment rates, etc. They may be carried out independently or at the request of a company;
- data from online forums and customer recommendation or review sites: to find out about the issues and concerns of Internet users, perceived brand awareness, consumer trends, etc.
Faced with this massive amount of data to exploit, it is becoming 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. So how can we achieve this?
How can Big Data be used in digital marketing?
Web tracking and retargeting to optimise the customer journey
✅ Big Data helps to harness information at a very fine level of detail in order to :
- Discover user behaviour across all digital channels: you analyse 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 aim? Better target your buyers and provide them with an ever more personalised offer thanks to a multi-channel and omniscient vision to provide offers tailored to the right target, on the right channel and at the right time, and identify any 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
- the sites visited
- the pages consulted
- actions taken on your site (buttons clicked) or lack of action.
Retargeting offers targeted advertising to Internet users who have left your website without taking any action.
🛠️ Web tracking 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 can be automated to increase efficiency and produce value.
You create scenarios of fully automated email sequences to provide contacts with content and messages that help them mature in their purchasing journey, after segmenting your contact base for more effective targeting.
This marketing software is interconnected with your CRM to update contact information, perform cross-checks and effectively monitor the customer relationship, from prospect status through to customer loyalty.
🛠️ Marketing automation platforms such as Webmecanik or Plezi can be used to exploit the information gathered on your website via forms, in exchange for downloadable white papers, for example.
Predictive marketing to anticipate user behaviour
The aim of predictive intelligence is to exploit large volumes of data collected from prospects and customers to make predictions.
Analysis of this data enables us to :
- gain a better understanding of buyer/user behaviour ,
- anticipate their needs
- sketch out future trends so you can 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 data to be collected, analysed and used across a range of channels to extract customer insights. Campaigns can be enriched with precise data to better anticipate the actions that customers will take. Combined with the other modules, it leverages the full wealth of marketing data to become a truly omnichannel customer engagement platform.
Datavisualisation for intelligent data reading
Using artificial intelligence and machine learning, datavisualisation makes it possible to make the most of data to understand it better and draw out relevant analyses:
- study your targets
- identify your market environment
- make forecasts, etc.
It provides a clear and relevant reading of essential information and makes it easier to manage your actions effectively.
🛠️ 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 analyse it seamlessly.
Semantic and emotional analysis to understand web users
The concept: scan the web, opinion 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 an influx of data that is 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 need to be respected in all circumstances, with "privacy by design " considerations being taken into account from the outset in order to build compliant information systems. While companies are equipping themselves with technologies that enable them to collect, integrate, sort and analyse high-quality information, they have a responsibility to think about and organise 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 information systems department and your DPO to ensure that data processing is compliant. .. and therefore worry-free.
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