Revenue from every customer is a return on the marketing investment used to acquire the customer in the first place. The impact that personalisation brings compounds at every stage of the user journey to ultimately make a massive impact on the return on marketing investment.
A typical business has 5 stages to it's customer journey - Awareness, Evaluation, Purchase, Use and Advocacy. The above infographic demonstrates the impact of employing personalisation at every stage of the user journey.
Video marketing as a content marketing strategy is inevitable. As an online business if you aren't doing video marketing you stand to lose and lose big. 2017 is going to be the year of video marketing. Over 55% of people watch video content online every day. 78% of people watch videos online every week. These people just don't watch videos for a couple seconds but according to research, 65% of video viewers watch over 3/4th of a video. As the trend for video content is on the rise, the research predicts that this year the online video content will account for over 74% of all web traffic. Cisco observes similar trends. Content in the form of video tends to swamp people's mind to feed their need for information and entertainment. Companies that fail to include videos in their content are trailing behind ages. Companies that have included a piece of video content in their landing page have increased conversions by 80%. The number of unique visitors on YouTube has reached a glorious one billion per month. It is next to impossible to attract such huge numbers with obsolete content. Pumping in new content frequently and subsequently managing this content is the formula one needs to follow to stay afloat. The next question would be, "Is this manually possible?" Of course, not, manually handling this magnitude is not possible.
Automated video content management
Content publishers and streaming platforms provide infrastructure to host and stream videos. There is a strong need to personalize content based on user behaviour through data intelligence. Automated intelligence in this way saves time and effort by managing and updating content irrespective of the volume and frequency. Managing video content is the strategic roadmap for providers of Digital TV. An online management platform (OVP) makes sure that the right content is sent out to the appropriate end-user at the right time. But not all the systems work alike. In general, most of the businesses prefer to work with the traditional web content management system to manage their video content. Later to realise they are not as effective as content management system specific to video. A video content management system assists in every way. From the most fundamental step of video uploading to providing a customized video experience. Automated intelligence helps to centralize and manage data. This also enables businesses to use the data to analyse the behavioural cues of customers. Thus, providing content that corresponds to their behaviour. Data intelligence and algorithms can help personalize videos based on customer behaviour. Your business' ability to make something uniquely customers', the more likely they will buy it. Videos can be personalized, and visually engaging content can boost performance on all kinds of metrics. Following are few ways to personalize content with videos.
Role of Personalisation in online shopping
"Let's go shopping" Nah. Who wants to step out in this congested traffic and go to a store with such limited and impersonal options? Few prefer the brick-and-mortar stores for shopping today. The tech-savvy world has shifted to online shopping, some time ago. Reasons are many. More options, ease of shopping, discounts, etc. Although, one thing that is not on the top of the customer's list of reasons and yet is a powerful motivator for online shopping is "personalized shopping experience". According to a report by Total Retail 2016 by PricewaterhouseCoopers, retailers who do not meet the evolving customer experience witness significant drop in sales. Customers expect the retailers to understand their ever-changing needs and plate up a personalized experience. As attention spans of the customers go lower and the diversity of customer preferences go higher, personalisation becomes the need of the hour.
Role of Data Intelligence in e-commerce
Larger e-commerce companies set up their own internal teams of data scientists. These teams help analyse and understand the end-user behaviour. Data intelligence, though shouldn't be confined to just confined to the big players but to every e-commerce company irrespective of the size. When companies do not have the luxury of time and money to set up their own teams, our expertise is sought after. We work with such companies to design and personalize the purchase experience of end users on their e-commerce portal.
According to MyBuy's 2015 Personalization Consumer Survey, consumers purchase more from brands that instil the following in their marketing efforts:
Recommend products based on browsing or purchase behaviour (53%)
Personalized content in online ads that promote offers and products (49%)
Personalized emails based on the shopping history and browsing patterns (48%)
Personalized the shopping experience across multiple channels (48%)
The data that revolves around the customer's behaviour online is spread across:
Social Media platforms
Our high-end data management platform acts as a one-stop storehouse for data from the above sources. Primary information like the name of the customer, purchase history, phone number and other data are aggregated from these sources.
Natural Language Processing (NLP)
When we need advice on some specific shopping tips we turn to our friends and family. Similarly how about seeking advice from our "machine friend?" Sounds cool, right? This is where Natural Language Processing(NLP) comes into picture. Through NLP, the machine understands the context of the content. It may be overwhelming to understand the changing human needs and be proactive to fulfil them, but through NLP the nuances of every item a user interacts with is understood. Ultimately, the uniqueness of NLP is providing a better understanding of the customer's needs and behaviours to the retailers. How NLP helps collect customer behaviour data is mesmerizing. Customers are on social media and on various forums expressing their views and comments about products and brands. Computers are programmed in such a way that they can categorize the frequently used words by customers into different topics. For instance, if the computer spots words like "quality", "performance", "durability" it is categorized under a topic "Product attributes". These topics give an idea on what that customer has on mind. Machines can never compete with human intelligence. So, the search terms fed into the program should be very flexible rather than immutable words. E-commerce portals and retailers should have access to efficient personnel who can handle the NLP efficiently. The better the companies are at doing this the better they can understand the customer behaviour. Various applications are being developed to answer the customer queries using natural language. As the world is turning to artificial intelligence it is high time e-commerce companies become proactive. The customers should not miss the experience of being attended to by a salesperson like in traditional shopping. E-commerce websites should be ready to play that role and satisfy them, unless they want to lose customers to a competitor who does. Our platform uses Natural Language processing and Machine learning to understand user preferences through the content semantics.
With the decline in television as a viewing platform and the rise of mobile streaming platforms, content providers need to make dramatic changes to stay in the game, and this is where big data comes in.
Many major players have been embracing Big data, and for a good reason. Let's take a look at a few stories.
The Example of Netflix's House Of Cards
Netflix has made very intelligent use of big data for content delivery on their platform. They analyze their subscriber behaviour routinely to gain an understanding of their preferences and affinities. The insights were fascinating - they didn't just find out that many of their subscribers liked Kevin Spacey (lead actor in House of Cards), but they also knew who exactly these people were and they used this data to directly target those fans by creating nine separate trailers of House of Cards, targeting these towards those users only. In short, with detailed customer data, they were able to create a better marketing strategy for managing the content (House of Cards) on their platform. Several other companies in the media industry like Spotify, and Amazon Prime are leveraging big data for analysing content and users to offer the consumers targeted choices instantly.
How Can Big Data Help Manage Content?
Big data helps you to know what exactly the content consumers are looking for, and helps you deliver more relevant content. Here is how it breaks down and here's how our data intelligence services can help you.
It provides real-time recommendations
Today's consumer looks for not just quality but a rich experience. Hence streaming platforms gain more popularity when they let consumers instantly access content that they would be interested in. Using big data analytics, streaming platforms can make relevant recommendations to the consumer in real-time.
With insight into the preferences of the consumer, organizations can carry out highly targeted campaigns and personalised promotions. Customers get the feel good factor when dealing with someone who knows their needs. Content promotions become less spammy and more relevant and ultimately enrich the customer experience.
Acquisition of the right kind of content
Streaming companies can acquire the right content which strikes a chord with consumers. This content can be further catered and personalised for the various segments of consumers. Big data helps companies make the choice.
How Can You Capitalise on the Trend?
If you've a content channel, and want to edge past your competitors, it's time to move the data analytics way. In the past few years there has been a vast increase in the number of videos that various brands and media companies have published on Facebook. YouTube is no longer the single video streaming provider. Facebook and Snapchat too are in the race and have been able to offer the customers just what they need. Live Streaming is the new focal point for all of them and is on the rise. They have extensively made use of analytics and tracking, gathering data from likes, views for their content creation strategy and managing that content so that it can be specifically targeted to the right customer at the right time. Every platform is upgrading their game based on the insights they gain from big data. YouTube is relying on the stars it created by driving loyalty. Facebook is providing a platform for companies to share content with their customers. Snapchat continues to make use of its exclusive content and live coverage to promote video content among its users.
Time to Start Your Data Intelligence Journey
Big Data has provided various architectural options for all kinds of streaming platforms to manage their content in a better manner. Why should you be left out? Help us give you higher views and better content optimization. Our data intelligence services will help you to understand content consumption so that you can tailor content according to user needs. You get real business insights and our Content management system helps you, all along the way.
Are you getting the right returns on your brand marketing campaigns? It doesn't matter whether you are using Facebook or Google to promote your services and improve brand loyalty, what only matters is that you do it right. With Facebook, for instance - while you can spend hundreds and thousands of dollars on marketing, what really counts is who you're pitching your ads to. Understanding your audience and user behaviour doesn't just require innovative marketing strategies but greater insights and you need data for that.
Big Data and Brand Campaigns
While marketing may involve a lot of art, to succeed, you need to base your marketing decisions on solid information, something that big data can help you with. Data intelligence has literally revolutionized the world of marketing and sales and changed the way branding is done. Here is an overview of how it helps your brand campaign do better:
The foundation of any marketing campaign lies in its market research - in the data that is collected to check the temperament of the market, for which the campaign is designed. Businesses can now conduct market research more quickly and efficiently using online tools and running the data that is collected through analytics tools for easier parsing of results and their implementation into the campaign. It also helps collect and analyse the data about the competition. Businesses can also refine their strategy to create a better pricing plan for improving profitability.
Big data helps in better allocation of resources and budgets dedicated towards marketing campaigns, so that they can be optimised and monitored in a better manner for the best return on investment.
Managing Brand Reputation
Big data has enabled companies to pull insights into who their customers are, where they hang out, what kind of purchases they make, how often and several other such factors. It also helps in analysing how the customer is interacting with their online store or website and with this they can create campaigns that foster better customer engagement and responsiveness which in turn will lead to more brand loyalty and customer retention. It solves the biggest challenge of marketing ie improving customer experience.
Online Marketing Campaigns
The biggest impact of big data is in the arena of search engine optimisation, email and mobile marketing. Big data is essential to these marketing strategies.
Predictive Lead Scoring
Lead scoring is used to generate ratings on the hottest leads, but big data has ushered in the era of predictive analytics which can create models that can predict the behaviour of buyers and the projected sales.
Real-Time Applications of Big Data in Marketing
Big Data is the buzzword in the field of marketing and several organizations have leveraged it to the fullest. Amazon for example, sells customer data to third-parties empowering them to market themselves better. Netflix has developed an algorithm to drive recommendations with real-time processing, turning customer actions into experiences -better ones, and it seems to be working well for them. The Financial Times uses audience data to push their circulation. They have teams that specialise in the domains of Data Analytics and Campaigns, Data Technology and Data Product Development which map reader behaviour, analyse this data to convert them into subscribers.
Big Data Has changed the face of Marketing
The marketing field is probably the one making the most of big data and reaping the opportunities it presents. Big data can manage each and every aspect of Marketing and branding helping CMOs and Marketing managers make more informed decisions.
How Can We Help?
At RecoSense, we help Brand Managers and Ad Agencies with design effective campaigns that are more target driven by using data from multiple sources and applying the insights generated from it in the campaign. We have essentially created marketing intelligence. Let us help you get the complete insights on the market so that you can create a campaign that can give you optimal results.
Every company in the market understands that there are 5 stages in User Journey. But, what they fail to understand is, how personalization can add value to their marketing in each of these stages.
In the ever evolving world of business, Loyalty and Retention are often used parallelly, but decisively they are not the same. We need to understand that both are valuable aspects in a business, but often these terms are mixed-up.
Does spending millions on Ads earn you loyalty or does it add revenue through customers? About 50% of Ads clicked or viewed are accidental. Ad Marketing is like fuel, the more you spend the more it burns. Customer tend to stay retained only when you know where to spend, when to spend and how much to spend. PageFair quoted " Ad blocking grew by 41% globally in the last 12 months".
Growth Hacking is the knack to acquire or retain 1 new/old customer. Growth hacking tactics aids in reducing the cost per acquisition to close to $0. It helps companies to grow ridiculously fast and acquire millions of users and dollars in revenue.
Growth hacking is not about plug-and-play, it's about evolving and tailoring hypothesis specific to your product and market. Growth Hacking prioritizes minimum effort with maximum yields.
The magical success formula which businesses have discovered is to treat customers like guests and that no two customers are alike.
Growth Hacking Trick #1:Contact as a Real Person
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