Differences in Data

Have you ever been pre-judged by someone before they had a chance to really get to know you? When I look at where data-sets are today, that’s kind of how I feel. We are taking our best guest at personifying individuals based on a series of various data sets that semi-fit together. In our last blog we talked about the importance of content personalization. If we are going to get there, data interpretation is just as important as the data collected about a person.

Different Types of Data

Qualitative vs. Quantitative

The biggest distinction in reading quantitative vs. qualitative data, is whether something can be easily categorized or not. Quantitative data is data that can be categorized numerically. Your shoe size, your height, your income, your zipcode etc. etc. In other words, it’s the demographic information that can be easily collected.. Qualitative data, however, cannot be categorized numerically. In the words of Isaac Newton, “every action causes a reaction”. This reaction, or emotional response can be classified as qualitative data.  

Target, for example, takes to the twitter-world to see the emotional reactions to new product launches. They collect this qualitative data about the individual responses to better understand their customers and move one step closer towards content personalization.

These two data sets go hand-in-hand because you can infer many correlations such as, location eludes towards cultural responses, affluence levels indicate certain buyer behavior, and so on.

First Party Data

Finders keepers! Anything you collect about your customer, is yours to keep. This means your brand gets the first glimpse into your customer’s interaction with your brand. First Party Data is one of the most valuable data sets because you can deploy any data aggregation strategy to understand the exact relationship between you and your customer during the buying journey.

For example, if you want insight into how your customers interact with your website, deploying a heat-mapping strategy to collect data on what images individuals click on might be the best route for gathering this first-hand intel.

Second Party Data

Second party data is like the ultimate tease. A customer may be in a data relationship with someone else, but you’re still benefitting from that relationship. For example, a customer releases the rights for Google AdWords to track their search history but you’re still benefitting from that same relationship with AdWords. It’s common for brands to strategically partner in a data sharing strategy to obtain information that otherwise might be too costly to collect on their own. This is why second party data becomes valuable, and knowing what data you’d need to further complete the personalization puzzle will help define the strategic partnerships you can create.

Third Party Data

This data is the most widely adopted data collection strategy. Marketers depend on data collectors to aggregate intel on customers that they can use to develop a variation of marketing strategies. Unfortunately for third-party data, it’s becoming less common in strategy development as marketers want more first-hand insight aka. first party data.

Knowing what type of data you are collection, can help you figure out what pieces of data are missing that will help you complete the puzzle towards content personalization.

References:

http://www.huffingtonpost.com/advertising-week/turning-intentions-into-c_b_8137128.html

http://www.getelastic.com/beyond-product-recommendations-big-datas-role-in-personalization/

http://www.b2bmarketinginsider.com/strategy/are-you-using-first-party-data-to-drive-personalized-customer-experience

http://www.emarketer.com/Article/Marketers-Put-First-Party-Data-First/1012663

http://marketingland.com/can-marketers-find-best-customer-data-noses-139308

http://marketingland.com/second-party-data-digital-marketers-128254

http://www.signal.co/blog/data-sharing-second-party-data/

Personalization is The New Nirvana

Digital marketing, such as advertisements, we see are like works of art. Creative directors are tasked with composing a variety of elements from realism to sound composition, to developing an advertisement that will grab your attention, keeping your interest, instilling desire, and demanding action. The difference between art and advertising, is art is meant to be enjoyable, whereas an advertisement is meant to fulfill a monetary purpose. In today’s digital world, creating advertisements can get even more complex, such as adding in a layer of augmented reality, that will engulf the targeted customer into an entire experience. The problem creative directors have, is to build multiple works of art that will appeal to a variety of different personalities to drive the same end goal.

Using Data to Develop Marketing Content

True personalization is creating a group segment audience of 1. This is also known as ‘nirvana’. The challenge that presents itself here is that no two individuals are alike. Even the most extreme identical twins have a small degree of variation in their personalities. I want to talk about a concept that I like to call ‘Deep Data’. I want to differentiate this from Big Data, because I think Deep Data as a descriptor to determine a person’s psyche.

There are plenty of Big Data sources available to help creative directors build ads based on high-level segmentation. Understanding demographics, can help creative directors determine basic cultural differences, and develop advertisements that will fit in various markets. Where it starts to become tricky, is gathering the deep data sources. It’s much easier to figure out where someone lives vs. the emotional intelligence of that individual. The other challenge, is most people are willing to give up demographical information, but any info that would be seen as compromising to the person is much harder to attain.

This is where digital trust is crucial if we want to progress towards true personalization.

Gathering Deep Data

Between beacons, IP addresses, learning algorithms, cookies and surveys there are plenty of strategic ways to gather information about a person. The problem, is all this data gets collected and stored in various systems and there isn’t a current solution that combines them all into one. The other issue presented here, is tracking the success of individual campaigns. There are ways to track open rates, impressions, click through’s and conversions, but what this data doesn’t tell you, is why an ad didn’t work with those that didn’t convert, and why it worked with those that did.

As we move towards Nirvana, creative directors and marketers will need to be able to understand each individual and know exactly which mixtures of messages and content will create the efficacy that every business wants without losing the consumer’s trust.

References:

http://www.forbes.com/sites/sap/2015/07/11/marketing-nirvana-engaging-with-an-audience-of-one/

http://searchcontentmanagement.techtarget.com/feature/Location-data-adds-context-for-Web-personalization

http://www.forbes.com/sites/johnrampton/2015/09/03/better-data-enables-better-customer-segmentation/

http://www.martechadvisor.com/marketing-analytics/clickagy-launches-data-driven-content-providing-intelligent-on-page-optimization-using-audience-profiles/

http://www.dtcperspectives.com/getting-to-the-how-unlocking-identification-personalization-and-the-regulatory-landscape/

Crossing the Data Driven Chasm

George Orwell in his book 1984, depicts a society that is overseen by Big Brother. Big Brother in this case, was the government. The Government, utilizing a series of various video monitoring services, were able to control societies every move. Now while 1984 is a tale of fiction, there is some truth to what he wrote. We are entering an era of information overload so companies can create individualized experiences and build one-on-one relationships.  

The Chasm

Chasm, by traditional definition, is a deep fissure in the earth, ie. a canyon, gorge or abyss. In Geoffrey Moore’s book “Crossing The Chasm” he refers to the pivotal moment in which high-tech companies cross the marketing chasm from early adopters to widespread adoption.  

Crossing The Data Chasm

Creating the ToolKit

You wouldn’t cross the grand canyon without the appropriate tools, so why try to develop one-on-one marketing without the proper data sets? Currently on the market, there are various resources that when coupled together get you further to crossing the chasm. For example, pairing implicit data sets from Acxiom with explicit data sets from Keen.io will help you profile your audience while analyzing what they visit most on your website to better understand their interests. However, these sets together, will only get you so far and you’ll probably still fall into the chasm at some point. What this data doesn’t currently do, is offer the ability to import into a SaaS marketing technology like Salesforce, Marketo or Mailchimp, to create individualized profiles. When this can be done, we will be much closer to content personalization and crossing the data driven chasm.

Skills Needed to Cross

Data is useless if marketers don’t understand what it means. If we pack the right tool kit to help us cross the chasm, it won’t mean anything if we can’t figure out where the chasm is that we need to cross. Early adopters that are closer to crossing the chasm are the digital media and technology agencies that are experts in finding the channels, and creating interactive experiences with their audiences. There is a great data divide, however, for smaller businesses to effectively deploy the right toolkits needed to optimize their advertising efforts.

The Data Chasm continues to grow deeper as more data than ever before is being collected through sensors, wearables, tracking and more.The race to cross the chasm has begun, and what we will see happen is the puzzle pieces come together to create the perfect toolkit.  

References:

http://businessvalueexchange.com/blog/2015/07/09/open-data-drives-us-towards-the-information-chasm/

http://exelate.com/resources/news/new-iab-study-reveals-data-divide-early-adopters-leverage-cutting-edge-opportunities-in-marketing-data-but-barriers-remain-to-broader-use-of-new-practices/

https://gigaom.com/2014/05/06/5-technologies-that-will-help-big-data-cross-the-chasm/

It’s Getting Personal

I’ve been reading many articles on data personalization as it relates to content marketing and I keep arriving at the same conclusion – It’s all about the story. But what story are we actually telling? A person doesn’t just have one story, they have multiple stories. Trying to reach someone when they want to be reached can get tricky. Are we appealing to them when they are working? Or do we try to reach them at home? These are questions data is hoping to help answer.

The B2B Story

You arrive at the office and you’re immediately bombarded with emails that never seem to end. You get called into your morning meetings where someone in the room is trying to ‘sell’ something – an idea, a campaign, a new tool that the company should buy, etc… Before you know it, it’s time for lunch. While at lunch you login to Linkedin and you’re flooded with even more ads – new job offerings, new services, new startups, etc…

Remember the famous quote: “It’s not personal, it’s just business?” While reading an article on B2B content personalization, the core message became clear; before you waste precious time on that powerpoint, find out how your boss wants information delivered. Marketers are presented with the same challenge. When creating the B2B message – find out exactly how the target audience wants information delivered. This will save you ample amounts of time in delivering the right message at the right time to the right person, because after all… time is money.

The B2C Story

You get off of work, and now you’re just an ordinary consumer faced with an amplified amount of places or things to spend your hard earned money. In our last blog, we talked about the importance of data personalization and why consumers want individualized messages, so it resonates as an emotional and relevant message.

If you aren’t familiar with Simon Sinek, he is famous for his Ted Talk on the ‘What’ vs. ‘Why’. He explains the seduction involved in storytelling and describes the brilliance behind Apple’s marketing messaging. Where Apple has the competitive edge over many businesses from access to their unique data asset. They understand their consumers so well, that their messages dig deep to connect with who they are… because ‘It’s all about me”.

The Differences in Constructing the Story

There are two main differences in B2B and B2C data. B2B data is more quantitative or objective in purpose, so it is typically used for lead generation. B2C data is more qualitative or subjective and help marketers piece together profiles to understand who you are, so there is more of an emotional connection. The ultimate goal in marketing, would be one-on-one, aka. personalization. When constructing these stories, it’s important to remember that people don’t become an entirely different person when they bounce from their B2B to B2C roles. To gather all of these puzzle pieces, it’s either ridiculously expensive or the data sets are very jumbled. The solution would be to have a robust platform enabling marketers the flexibility to select the correct data sources to construct the compelling marketing messages that they can apply to their target audience, at the times in which they would like to be reached.

Data still has a far road ahead for marketers to reach personalization, but we are slowly crossing the chasm to deliver the optimal value for their end customers.

 

Resources:

http://m.bizcommunity.com/Article.aspx?l=196&c=423&i=132915

http://techcrunch.com/2015/08/14/the-future-of-consumer-marketing-is-personal-2/?utm_medium=referral&utm_source=pulsenews

http://www.business2community.com/b2b-marketing/b2b-personalization-is-still-far-from-wash-rinse-repeat-mode-but-you-can-create-the-right-framework-01280978