Notorious Big Data: How Should We Be Using It?
No one knows more about audiences than Netflix, and no one publishes more than the NY Times, and according to them “a third of the downloads on the Internet during peak periods on any given day are devoted to streamed movies from the service. And last year, by some estimates, more people watched movies streamed online than on physical DVDs.” But how do we analyze all this data? By gathering big data!
Big data has become very important for major companies as it has revolutionized marketing in many aspects. Today, brands can analyze and learn more about their target audience, competitors’ strategies and industry conditions. That’s why a true marketing team need to leverage big data analytics as it is developing a campaign. But to do that, every marketing specialist first needs to understand the four major Vs of big data: velocity, volume, variety and veracity.
Secret Ingredient
However, having big data doesn’t necessarily lead to better marketing. Big data is more of a secret ingredient to season your marketing game. You can’t solely use data and expect instant high ROI; rather, it’s the insights derived from big data, the decisions we make and the actions we take that make all the difference.
Three types of big data are crucial for marketing:
1. Customer: Includes behavioral and transactional metrics from such sources as marketing campaigns, points of sale, websites, customer surveys, social media, online communities and loyalty programs.
2. Operational: Includes objective metrics that measure the quality of marketing processes relating to marketing operations, resource allocation, asset management and budgetary controls.
3. Financial: Includes sales, revenue, profits and other objective data types that measure the financial health of the organization.
6 Elements
What series of actions should you take to ensure big data efficiency? Here are 6 elements you can check off your list:
- Successful discovery of new opportunities. You need to build a data advantage by pulling in relevant data sets from both within and outside the company. Analytics need to go beyond broad goals and get specific to better target buyers. Examples include: which websites a user visits most often, which social media profiles they use. In that way, the “ideal consumer profiles” can easily be targeted.
2. Understand consumer decision journey. Today’s fickle consumer is comfortable using an array of devices and technologies to get tasks done. Understanding that decision journey is critical for identifying battlegrounds to either win new customers or keep existing ones from switching to competitors. Marketing teams need to develop complete pictures of their customers so they can send out relevant messages. If properly executed, this action can greatly increase customer engagement, customer retention and marketing performance.
3. Track Google Trends to inform global and local strategy. Google Trends demonstrates trending topics by quantifying how often a particular search-term is entered relative to the total search-volume. Global marketers can use Google Trends to assess the popularity of certain topics across countries, or stay informed on what topics are top-of-mind to their buyers.
4. Create real-time personalization to buyers. Marketers need to send the right message at the right time. Timeliness and relevancy are the foundation of successful marketing campaigns, e-mail click-through rates and consumer engagement with your brand. In that regard, you can get timely insights and find out who is interested in the product in real time.
5. Identify the specific content that moves consumers down the sales funnel. Marketers can see the effectiveness of a marketing push down to tweet. Tools like content scoring reveals which individual content assets are successful to a closed deal. This allows marketers to change the strategies around the content topics that resonate with consumers the most.
6. Make it quick and simple. Companies need to invest in an automated algorithmic marketing, in order to create more relevant interactions with consumers. This can include predictive statistics, machine learning and natural language mining. These systems track key words and update your content based on changing search terms used, ad costs or consumer behavior. It can make price changes on the go based on customer preference, price comparisons, inventory and predictive analysis.
All in All
“Data can only tell you what people have liked before, not what they don’t know they are going to like in the future”. That’s why, a marketer shouldn’t just rely on big data analytics to drive growth for the future. Having said that, the implications of these listed actions will surely increase over the coming years. But right now, big data is already in use, and it is incredibly valuable to the entire marketing process. So, know your Ps and Qs, and keep tracking how big data is evolving.
To cap this week’s blog, I am leaving you with a quote by Albert Einstein:
“Imagination is more important than knowledge. Knowledge is limited. Imagination encircles the world.”
