The connections between marketing and Big Data are easy to see. GPS tracking devices provide the location of people who use certain smartphone apps. Facebook and Twitter are huge databases of people’s behaviours and attitudes and search engines record people’s daily activity on the web.
That is why digital marketing professionals believe that Big Data is essential for an effective marketing strategy.
Marketing has evolved tremendously over the years, largely because technology has enabled it to reach, when the situation calls for it, either a bigger audience or a more specific, targeted audience. This has helped businesses reach audiences at much faster speeds and lower costs than more traditional advertising methods.
The digital age has brought with it huge volumes of data. Big Data offers great insight which can be used by the marketers to make better marketing campaigns. A direct benefit of this is that the companies can develop better strategies with the help of these insights and thus target the core need of the audience. This will allow digital marketers to acquire better insights and transparency about their customers.
However, marketers are slowly embracing the concept of Big Data, with its ever-increasing challenges. We are in the digital era, with so many gadgets that we use on a daily basis to keep track of our fitness, appointments, expressing ourselves on social networks, smartphones, apps, etc.,
All this data can yield product insights, allowing businesses to create products and tailor their services to what their target demographic wants. It can also help them understand how to effectively communicate the value of these products and services, optimize their distribution strategies and determine the right price to ensure a healthy profit. All in all, the more data you have, the more informed decisions you can make.
As the world becomes more digital, enterprises have enormous data to deal with. Big data pulls out all the valuable data that can trigger company’s benefits. Big Data plays a key role in digital marketing strategy.
What is big data?
Big Data is a term that describes the large volume of data – both structured and unstructured – that covers business activity on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analysed for insights that lead to better decisions and strategic business moves.
As the word Big Data itself implies that it is a data-set which deals with large chunks of digital data. This digital information can be anything ranging from sales information, online consumer data, mobile data, social media and more. Manufacturers and service providers collect these from various agencies and make use of this information for promotion of their products and marketing purposes.
They make use of analytics and take services of experts to devise a marketing plan and strategy which helps them to use this data in an optimum manner and reach out to maximum number of people. By planning in this manner companies can reach out to their target audience in a better and efficient manner.
The impact of big data in digital marketing
- It helps target your audience
Besides the ability to engage an audience on a large scale, Big Data can also be used in creating personalized campaigns targeting individuals – marketers can recognize significant patterns of consumer behaviour which will help to engage audiences at the individual level. Therefore, knowing it’s potential and integrating it into the operations has helped organizations discover how to build an advanced branding for the long run of their business.
They are now able to target consumers not only as large groups but also as segmented sub-groups with their own specific features, which gives them the possibility to modify activities and adapt to each one of these audiences individually.
- Identifying new customers
Big Data, especially information stored by social networks, introduces marketers with great detail of consumers’ behaviour and interests. This enables marketers to add more variables to their audience targeting. Traditionally, marketers only used demographic terms for targeting their customer base, which usually includes: age, location, marital status and education. Now with increased number of parameters provided, marketers are able to identify more customers who would be interested in buying their product and target their audience much more accurately than before.
For most businesses, one of the most important tasks is to enhance customer experience. Especially nowadays, due to heavy competition, it is very important that companies know on a whole, what their customers are thinking so that they are able to retain them. Immediate tweaks and turns can be applied and changes can be implemented to leverage the customer.
- Data-driven strategies
Modern customer analytics tools enable marketers to segment their customers into micro-targeted groups based on behaviour, not just gender, age and interest demographics. Combining such metrics as sentiment analytics from social media with CRM data, marketers can create a more holistic view of a customer’s lifetime value and then improve up-sell opportunities.
User experience is one of the basic preconditions of a successful business. In the era of Big Data, marketers are enabled to customize operations and improve customer journeys almost to the point in which every single client receives products or services based on his/her personal preferences.
- Real-Time Personalization
The concept of customer personalization has been around for more than a decade by this point. In spite of this, only recently have marketers been able to offer an authentic personalized experience to consumers, based on interests, preferences, and real-time behaviour. Thanks to Big Data, marketers now can deliver relevant content to their website visitors, based on where they clicked and where they came from.
- Marketing analytics
Marketing analytics used in conjunction with big data will help many organizations properly evaluate their marketing performance, gain insight into their clients’ purchasing habits, market trends and needs and make evidence-based marketing decisions.
- Enhance equipped to target
Once the marketer successfully gains an accurate and deep understanding of their audience’s behaviour they can strategize how to make use of the existing data and insights and how to impart it into their digital marketing operations.
- Uplift the sales chart
Big Data has automated the entire sales activity and helped marketers to create more effective algorithmic marketing model for their business. This approach helps marketers to set campaigns targeting the right audience by using behaviour match analytics. It also empowers digital marketing leaders to spot the prime time and different ways to reach their potential and existing customers. Besides each customer, their specific interactions are stored in the organization backend. This data can be used to retarget based on the purchase history and also enhance sales opportunities with cross-sell or upsell approach. Given the cost and legwork involved with leveraging big data, there should be a financial incentive
- Finding new marketing opportunities
Products need constant upgrades and big data analysis can provide marketers with patterns that can be used for improving their existing segments or features and finding new marketing opportunities. Data science is capable of analysing current marketing strategies but it also has the ability to successfully predict future trends. That’s why marketers utilize it to create business forecasts, which allows them to behave proactively and go one step ahead of the competitors. In the environment of constant struggle for more market share, this big data feature turns out to be essential for many companies.
- Making more profitable ads
We already talked about improved audience targeting opportunities that big data analytics offers, but there’s much more to this. Information gained from social networks and search engines can be used for creating more attractive and effective ad campaigns.
If a marketer knows what consumers are looking for they can create more suitable ads. If targeted audience is doing frequent researches about low cost flights, marketers can add promotional ticket prices to their ads.]
- Measuring campaign results more accurately
Big data sources can also be used for measuring campaign performance and effectiveness of individual media channels. Accurate campaign results can save plenty of company’s funds intended for future campaigns, by directing it to the media channels and ads that offer the best performance.
The data-driven approach allows companies to look in the past, pick up what has worked, and see the impact of it in the future in a simulated environment and based on the desired results apply the strategy. This is what predictive analysis offers you.
- Measuring ROI
Surprising as it may seem, many marketers actually don’t know how to measure ROI. Big data eliminates this problem: it takes into account all marketing channels, activities, and investments and conducts a cost-benefit analysis of each element. This way, it is almost impossible to misinterpret your marketing activities and the corresponding budget.
What do big data strategies include?
- Sentiment analysis
- Soft surveillance and consumer behaviour tracking within retail stores
- Open communication channels with clients
- Predictive analytics (which can monitor inventory levels and ensure product availability)
- Analysis of customers’ purchasing behaviours
- Response to value-added services based on clients’ profiles and purchasing habits
- Effectiveness of real-time micro-segmentation of clientele targeted with custom tailored ads
Different Sectors: Different Uses for Big Data
The data that must be captured varies for marketing purposes.
For online retailers, Web server logs, referring sources, page views, navigation patterns—basically all activities on the website—would be very beneficial. This lets retailers identify what keeps clients interested and what pushes them away. For some retails, there’s even the potential to mine a visitor’s historical browsing patterns and searches and display items that she might have previously been interested, as well as similar items that will likely interest her, when she returns to the site.
For brick-and-mortar retailers, on the other hand, face a different challenge. Loyalty cards have been, and remain, a popular method to capture shoppers’ behavioural data. However, as stores increasingly offer free Internet to their customers, as well as mobile apps that provide electronic coupons, this provides data of great value to the retailer (not to mention a helpful service to the customer). Behind the scenes, the app gathers information that will help create a profile of the shopper. The app can also increase sales through the use of display ads.
What are the benefits of Big Data to marketing?
Likewise, there’s an expectation for marketers to use data analytics to capture leads, fine-tune their campaigns and ultimately grow the bottom lines of the businesses they represent. Each of these points speaks to the need for marketers to make data-based decisions versus trusting their guts. From increased opportunities to reach leads and increase sales to fine-tuning your existing marketing campaigns, many marketers have yet to tap into the power of big data. Yet if the upward trend towards further adoption of big data analytics is a sign of things to come, those who get on board today most certainly have an edge over their competition.
- Determining marketing campaign effectiveness
- Determining marketing channel effectiveness
- Tailoring marketing campaigns and promotional offers
- Determining customer value
- Doing finer-grained customer segmentation
- Predicting customer behaviour
- Determining which product features are called and not valued
- Determining the optimal time to launch marketing campaigns
- Monitoring customer and market perceptions of the company
- Discerning customer needs for new products/services
- Personalizing search results on a company’s website
- Monitoring and improving the customer experience on the web or mobile devices
- Comparing process with competitors
- Identifying new geographic marketing for existing products
- Marketing to consumers based on their physical location
- Understand competitors moves (beyond pricing)
- Monitoring and improving the customer experience in “offline” channels
What are the challenges with big data in digital marketing?
To that end, today’s marketing departments face many challenges. Organizations are still identifying methods to make their products more customer- and market-driven, while businesses are pressured to drive more qualified leads to their sales teams and to work with product development to ensure they’re delivering the products and services clients are asking for. Some have identified marketing analytics as a way to resolve these challenges.
Although big data has uncovered new opportunities for businesses to reel in revenue, it’s also created a slew of challenges for marketers.
- Being able to handle the large volume, velocity and variety of big data
- Find the optimal way to organise Big Data activities in a company
- Getting business unites to share information across organizations silos
- Reskilling the IT function to be able to use the new tools and technologies of Big Data
- Understanding where in the company should focus on Big Data investments
- Finding and hiring data scientist who can manage large amounts of structured and unstructured data and create insights
- Building high levels of trust between the data scientists who present insights on Big Data and the functional managers
- Putting our analysis of Big Data in a presentable form for making decisions
- Getting functional managers to make decisions based on Big Data, rather than on intuition
- Determining what data to use for different business decisions
- Getting the IT function to recognise that Big Data requires new technologies and new skills
- Determining what to do with the insights that are created from Big Data
- Determining which Big Data technologies to use
- Keeping the data in Big Data initiatives secure from internal parties
- Keeping the data in Big Data initiatives parties
- Keeping the data in Big Data initiatives secure from external parties
According to analytics firm SAS, the most common problems presented by Big Data to marketers are three-fold:
- Knowing what data to gather. Data, data everywhere. You have enormous volumes of customer, operational and financial data to contend with. But more is not necessarily better – it has to be the right data.
- Knowing which analytical tools to use. As the volume of big data grows, the time available for making decisions and acting on them is shrinking. Analytical tools can help you aggregate and analyse data, as well as allocate relevant insights and decisions appropriately throughout the organization – but which ones?
- Knowing how to go from data to insight to impact. Once you have the data, how do you turn it into insight? And how do you use that insight to make a positive impact on your marketing programs?
Required tools and skills for digital marketers
Finding tools that will make big data more accountable is another very important requirement. Some of the most widely used big data tools are:
- Business intelligence tools- enables marketers to retrieve, analyse and transform data into useful marketing information;
- Predictive analytics tools- help marketers to extract valuable information, determine patterns and make predictions;
- Data visualization tools- are used for making easy understandable graphs and charts;
- Marketing automation tools- used for running marketing campaigns through many different channels;
Businesses are going to implement lots of investment in Big Data in the coming year. Though the investments might vary from enterprise to enterprise, the investments on Big Data are going to discharge a higher return on investment (ROI). After all, data-driven marketing has become the norm of today’s businesses. Rather than trust assumptions or gut feelings, modern marketers are making decisions by the numbers available to them.