You clicked on a classy pair of denims while surfing the Internet, and now the product keeps popping up on your social media pages as if luring you into making the purchase. What now? You try to dissuade yourself from buying that awesome pair to the best of your abilities. In the end, you manage to stop yourself from buying it. Right? Probably not. It is sometimes impossible to not fall prey to these stubborn ads. In 2013, online tracking and targeted advertising practice helped Internet advertisers rake in a staggering $42.8 billion. And for 2014, that climbed to $49.45 billion, or a 15% jump. Analytics is the key that lets the ad network know where you are so it can send you personalized ads.
Analytics is now making customers’ lives easier and creating a more happy and loyal customer base. Author and consultant Geoffrey Moore said, “Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.” His words lay stress on the significance of analytics when it comes to aiding decision-making and driving profits.
Data is the New Oil
Both small and large enterprises are now thinking about data monetization to generate revenue streams. Alibaba CEO Daniel Zhang recently told an audience at Nielsen’s Consumer 360 Conference that the Chinese e-commerce behemoth is focused on collecting consumer data. Zhang went on to say that data is oil in the new economy.
The concept is not lost on marketers who especially in recent years have been urged to squeeze data to better target customers. Even companies, such as Amazon, Google, LinkedIn, and Netflix, are all well known to monetize information to generate revenue and gain market share. Additionally, leading banks are using information about their customers’ shopping habits — how much they spend, where they shop, what they buy — to make money. Based on that data, retailers are offering targeted discounts via the banks through text messages, email, and online bank statements and ads. The banks don’t actually hand over your data to retailers. Instead, retailers describe what type of customer they’d like to target and the bank then sends the deal to customers who fit the profile. When the customer cashes in on the deal, the bank gets paid a commission.
Some online stores are even using phones’ Wi-Fi to track customers’ buying habits. All our smartphones are equipped with a Wi-Fi card. When this card is active and searching for networks, it is traced by local routers. At home, the router syncs with your device and you get Internet access. But in a retail environment, other in-store equipment can pick up your Wi-Fi card, learn your device’s unique ID number, and use it to keep tabs on the device as you move through the store. This gives offline companies the power to get incredibly specific data about how their customers behave. You could say it’s the physical version of what web-based vendors have spent millions of dollars trying to perfect — the science of behavioral analytics.
RetailNext, based in San Jose, uses video footage to study how shoppers navigate. For instance, it was determined that men spend only one minute in the coat department. Such insights were used to streamline the men’s outerwear layout. Similarly, Brickstream uses video information to watch shoppers. Cameras have become so sophisticated, with sharper lenses and data-processing, that companies can analyze what shoppers are looking at and even what their mood is. Even when you are downloading a retailer’s app, the retailer gets to know about your complete profile — your visits to the app, what products you were looking at, your purchase history, and so on. That’s when you start getting recommendations on your social media pages about, say, a gorgeous pair of Steve Madden pumps or Calvin Klein jeans.
Array of Opportunities
Today, more than 80% of data obtained is unstructured. Effective data mining and business intelligence operations open new avenues of analysis, thus allowing companies to come closer to its customers in real time. By successfully understanding data, companies can identify trends, create new products and services, and in the long run, make decisions and strategies that are supported by both structured and unstructured data. Marketers can add immense value using customer data and create spectacular advertisements.
Along the same vein, data enables an enterprise to devise a strong marketing strategy and create customized content for their target audiences. It enables them to deliver the most relevant content to their audience the way they want it and when they want it. In simple words, that’s data-driven personalization! Moreover, data-driven personalization bridges the disconnect between what retailers are providing and what their consumers expected. Personalization can make it easy to connect data about visitors — such as behavior or information stored in CRM — and use it to create experiences in real time. So, you see how data is driving the creation of giant strategies around monetization and customer impact.
BRIDGEi2i’s retail analytics solutions help retailers leverage the power of data to derive insights on customer behavior and develop a personalized customer-centric approach to product, marketing, pricing and channel strategy. Recently, BRIDGEi2i helped a US-based high-end fashion retailer identify high-value customers, enhance customer experience through touch point personalization, and maximize customer lifetime value. To know more, read the complete case study here.
Roadblocks to Data Monetization Strategy
Transforming data into actionable insights and generating new revenue streams is a challenge. Companies are keen to figure out how their business can be driven forward to create new avenues while increasing their revenue and growth by overcoming major quandaries involved in data monetization. One of the major questions they ask their service vendors is around how they can trace the risks and investments needed to build a data monetization strategy. These companies either grapple between understanding how to invest raw data for distribution and handling the sophistication around analytics or data processing.
Today, more people log on to the Internet, allowing brands access to more engagement data. But if a company does not have trained data analysts to revamp the way data is collected, stored, and analyzed consistently, there would not be any business rewards. As people change in the way how they engage, data analysis must also change over time. Companies tend to harbor thousands of individual data stores, which make it difficult to access data for monetization purpose.
Also, organizational resistance, overly conservative interpretations of regulatory requirements, an inflexible organizational structure, and an out-of-date go-to-market strategy can prove to be significant roadblocks for data monetization streams. In the process of monetizing data, getting an external perspective is important. Benchmarking of other institutions and effective data monetization strategies can help in framing new ideas and getting valuable insights.
Invest or Collapse
So, with this dependence on analytics and data, monetization of data is no more a far-fetched reality. There is undeniably still a great deal of unexplored information in customer feedback comments, video footage, conversations on the social media, and locational GPS data, which needs to be explored and utilized. Innovative and nimble approaches to applying analytics to data will certainly bring in loyal customers as well as generate maximum revenue without downturns.
Analytics has revealed how amazing data deluge can be when tracked at the right time. In the end, it all boils down to how you are turning data into information, and information into insight.
Sure you need to spend some money on analytics (technology and people), but it’s going to be less than the price you’ll pay if you don’t know how your business is performing.
– Arthur C. Nielson, Founder at ACNielsen
So, it’s up to you, will you treat data as an opportunity and invest, or will you allow it to go stale? Roll up your sleeves today and start contriving a strategy and carving a vision around the monetization of information and analytics.