How Social Analytics is Disrupting Customer Segmentation in Retail

Chasing the digital dragonfly: analytics of customer personas....hacking social for omni-personalization. Data mining to the rescue. 

What is your company's DIQ, your disruption innovation quotient?

Fair warning, this is going to be a long form post full of my personal bias and unbridled enthusiasm. It's Friday, after all. 

In 2016, the promise of increased customer personalization to create better omnichannel experiences is higher than ever. Millennials have pushed the expectations and data-science has opened up better social CRM, tagging, segmentation and persona building tools.  These are obviously invaluable to Retailers, Marketing teams and Small independent business owners alike. Just as small businesses are hopping on the cloud POS band-wagon, there are so many exciting developments. 

From your loyalty rewards campaign, to your Email and SMS marketing campaigns to your User Generated Content Contests on Instagram, knowing more about your customers, to build high value relationships, is more important than ever! 

What we are starting to notice here in Montreal, as more American startups migrate here (mostly from San Francisco and New York) for the fertile innovation and partners there is a new breed of persona mining tool, that centers less with the bells and whistles of a social dashboard and more along the lines of a Big data API, Macromeasures, is a case in point. As machine learning and Big data catches up with the Millennial movement that is sweeping social media, new companies will disrupt that way marketing teams can pinpoint that all import and elusive, and holy grail of customer data. 

For data savvy marketers, it's not the interface that matters, it's how many ways can you verify a persona and tailor your triggered Email, your customized loyalty program, your special promotion personalized to the high-value personas that count. Count for your brand, or store, or the high value customers you depend upon. The world is waiting for real-time personalization and it is close, very close. 

Next Generation Personas for Tomorrow's Personalization 

What this amounts to is not just gender demographics, sentiment analytics, or social channel determination, but details like brand affiliation, lifestyle patterns, vertical niche co-interests and tagging in ways that can be insightful in terms of their behaviour like favourite music, favourite TV shows and the kinds of insights that matter to how Millennial personas can be marketed and advertised to. In other words, the way we do persona profiling and learn about our customers is being augmented with smarter machine learning, more intelligent queries for analytics, etc. 

So what are we getting at here? This is where analytics and millennial marketing collide with data that is equally valuable to Retail, Marketing, Product Development and Customer Success. With data fields that have implications in Cost of acquisition, conversion rates, customer lifetime value, and the all elusive customer experience insights that translate into better products and boost sales. If you work in sales or marketing or retail, you are seeing $ signs here.:

• Customer insights 
• Big Data
• Demographics 
• Sub-Segments down to profiling your brand key top personas
• Psychographics
• Analytics
• Business Intelligence
• Predictive real-time marketing 
• Predictive analytics 
• Reaching the customer at critical phases of the buying cycle 
• Retention and loyalty reward campaigns 
• Millennial marketing 

Investing in a data tool, that has the greatest number of real-world applications and can complement other tools is then the makings of a machine-learning tool that improves the marketing IQ in 2016 and beyond.

Remember, at the pace machine learning is evolving, such a tool scales and adapts to the market in a dynamic way that can help Retail, Marketing and Small business owners "keep up" with the accelerating pace of change. 

Macromeasures helps brands understand their customers.

Data at the Service of Innovation 

Data at the service of niche industries is nothing new to Thirdshelf either, the way they create segments already maximizes ROI at the service of building high-value relationships with the customers of small to medium independent retailers. Their ability to automate and customize tailored loyalty reward campaigns with unparalleled mix and match strategies benchmarked to your industry verticals, means each of your campaign's ROI is optimized. Optimized  in a white label trust building manner that can growth hack an SMB's retail consumer audience. 

Thirdshelf  empowers indie retail to get tailor-made loyalty programs for their small to medium businesses.

Definition of a Viable Startup 

In my search for the most disruptive companies in Montreal, the first thing that struck me about Macromeasures, is how young and data-science focused the company is. A company culture tells a lot about it's potential evolution. Young Millennials plugged into Big Data better, obviously have a chance to disrupt the current players. You can get sales people, you can find the right marketing people, but those engineers, they are the gold that lays the foundation of your startup. 

There has never in the history of the Planet, been a greater need to gain psycho-social insights from unstructured data. 

This has always been the missing link with Big data and as social analytics evolve, this is going to become seamless leading to a vital predictive analytics embedded into everything. This is part of the internet of AI, that is a later part of how IoT evolves. We are starting to see the signs of how the route to get there could go. 

The Channel that Matters to Millennials 

The instantaneous aspect comes through SMS, the text message that we check, above and beyond all other channels like a phone call, like an Email, like a digital advertisement in our location. Only SMS is intimate, only IM feels real any more. But like everything in life, it's the relationship with people that truly matters.

That's why customer insight for SMB business owners, has to always be a consideration, especially in an age of cloud POS like Lightspeed, Vend and others. In this way, the way indie stores can attain personalization is fast-tracked and streamlined. Then we can assume, the cloud and machine learning both have huge implications in the evolution of personalized offers that feel authentic, that are intimate, that truly surprise, inspire and are unique and tailored for each persona, triggered to each person. 

Make no mistake, this transformation will come from young people, who will have to reverse-mentor us. Gone are the days that if you were a VP of marketing you have any true insight to how things work in the mobile world. It's only a matter of time before young millennial companies, disrupt their older less data-savvy rivals, the automation brands that are all bells and whistles. The substance, is always ROI, and because analytics is crucial to this step, companies that offer customer personas insights that are tired to data, have more innate potential. 

How to Measure a Startup? Evaluate their Disruption Innovation Quotient. The probability their solution can do better than what is currently available. 

As someone that cares deeply about startups that have a high disruptive innovation quotient (DIQ), I ask you, how old do these people look? 

They look like hustlers that would know a thing or two about #IlooklikeanEngineer . My favourite social media movement in tech, in 2015 via Isis Anchalee. These are the types of people I care about, these are the types of startups that will matter. 

As a freelance with considerable interests, I do not mean to be biased to companies located in my home city. For customer insights about personas, rest assured, there are dozens of tools.

Some that lean more on  social CRM dashboards, while others Big Data analytics. Still others, one channel wonders. But can social listening give you insight on personas or tangible data on sentiment analytics? I haven't been blown away, till now. 

While mainstream marketing tools like Google Analytics and Facebook show a lot of useful data on segments, they should not be under-estimated and will always complement data from other sources.

Since the reality is omnichannel, it only stands to reason that Retail, Marketing and business owners should combine their data from multiple sources for a more accurate frame of reference on their true personas, that may interact with their store or brand at different times in the season. 

While in 2014-2015, marketing automation systems were all the rage, I think in 2016, what we are going to see is marketing automation occurring with SaaSs that cover a niche better than the "big names" of marketing automation. Just as apps will evolve more intelligence for specific tasks and processes. 

Obviously a tool that excels at data-mining in via social channels, like Macromeasures, will give you the edge you need to know more about your personas, and narrow down your segments to more profitable personalized groups of similar customers. The debate about 1:1 segments and personalization probably doesn't even make sense, as a good ROI strategy, at least not yet. 

Social media tools simply don't have the machine-intelligence to take data from different sources and generate reports and insights that are useful to your omnichannel campaigns. Marketing automation platforms too have been built to integrate, have a comfy interface, but may not actually be as apparently "smart" as they claim. 

Is 2016 the Year Big Data goes Mainstream for Real?

What I see occurring in 2016, is Big data coming more to the mainstream, and these more gimmicky solutions losing in popularity as the digital reality basically accelerates past what they can offer. The two SaaS examples I have used in this article, can and will disrupt their respective niche unique selling points of loyalty and personas, respectively. SaaS or MAPs that give over-the-top promises about customer centricity, well, I don't tend to trust them. 

 I can't count how many marketing people I've spoken with who could not even tell me their top 5 personas of their customer audience are!. In 2016, that will no longer be acceptable. I'm no expert, but let me quickly shout you out some names that come to mind when we are talking about social and the dancing around the vicinity of how to find your brand's personas?

While reading these below, just keep in mind the future is about analytics, not about pretty interfaces or tools that claim to be able to do everything with saleshpeak promises. 

True 1:1 marketing has always been out of reach because there has never been a way to get accurate and individually granular data on who someone is and what they are interested in. We started Macromeasures to solve this problem.

The Macro Customer List - Software Tools 

Disclaimer: The below comments must have a twitter-esque all comments mine, not representative of any brand, company or person, other than myself.  Though you can see my bias for niche software, that covers a segment of marketing and automation well. 

• Macro measures: API based data-mining tool giving immediate customer insights. Tailored to lifestyle personas, Practically a Gen Z company hacking Millennial targeting. 
• Thirdshelf: Loyalty champion that champions SMB Retail. Focus on value segments via measurable ROI in $sales terms via cloud POS integration with customer success coaching. 
• InfusionSoft: For the SMB. Tries to be everything. 
• Pardot: Big Data analytics 
• Act-on: Email focused. 
• Oracle-Eloqua: Cross-channel unity data MAP. 
• Nimble: Social selling like smart, like nimble smart. Web copy has a lot of repetition. 
• LeadSquared: MAP
• Attivio: No comment. 
• SimplyMeasured: Your data visualizations look archaic, but useful. 
• Marketo: MAP, I've heard your name, you web copy is pure sales-shpeak. 
• Sysomos: Impressive value proposition, nifty branding. 
• HubSpot: Yes, you inspired us 10 years ago, or was it 15? Honestly I cannot remember. Though, I still have to take your free inbound marketing course. 
• Buzz Sumo: Dare I say content analytics?
• Google Analytics: The experts in this are still marketing wizards imho. 
• SocialClout: I appreciate the sentiment, I appreciate you mention "sentiment" analytics. 
• Facebook Campaign Analytics: How I do give you points for trying. 

We're developing technology that will allow us to understand more about the individuals inside of social networks. - Vasu Nadella, CEO, Macro Measures. 

Advent of Lifestyle Personas 

Their gender, location, what brands they like, what shows they watch, and what they are interested in...

It has occurred to me, values are what makes Millennials tick, the lifestyle identification of being young, of doing something in the world that has meaning, authenticity, connecting the dots that matter. We don't live to work, we live to be passionate about work that innovates and contributes to humanity, to community and to our collective well-being. 

The more I think about the analytics that will matter in 2016, the more I realize its these (lifestyle) we should be paying attention to. My attraction to FitBit for example, is a wide range of variables right, part quantitative self advocate, part failed fitness addict, full-on gamification enthusiast. 

When Retail, brands and business owners, realize the kind of segments that are most ROI salient, the long-standing problem will be solved. Not by people, or strategy, but by data, machine learning and better software - hybrid human-AI consciousness. As machine learning evolves, consider this, smarter software tools will become increasingly cheaper, in effect putting all these pricey MAPs out of business. 

Don't mind the rant.  Have a good weekend folks!