The Advent of Machine Learning as related to Social Listening

The advent of #MachineLearning as related to social listening precipitates a lot of honest-to-God hard work during a transition from human-led to machine-led insights. This will happen because many humans will be needed to create custom attributes and custom classifiers for the machine to use in the new upcoming #AI driven insights industry. Humans teaching the machine to think like we do, to analyze like we do, to understand nuance, culture and the evolution of language (keep in mind, social tech experts, I am referring to a truly global machine analyzing the languages of the world…not just English).

Since there are many gaps in social data, we face an uphill in pairing other data sources to the snippets we get from public sources of conversations. The key to a complete “AI Social Data Intelligence Machine” will be sources such as Axciom, census data, background check sources, private networks like Doximity/A Small World and finally, if possible, the nexus of data from Facebook and Amazon. This particular nexus is a kind of holy grail that the leading machine intelligence experts will eventually open to brand leadership. But previous to such events, we have a grueling journey as analysts, insights researchers and programmers to “teach the machine how to be a human”.

One of the most exciting branches of this “teaching” will be a self-aware machine, an artificial mind that will begin to offer recommendations…and then may decide to act upon these recommendations.

How To Perform Audience Intelligence – 2017



  • We discover your target audience and guide you in the best way to sell to them.
  • We connect you directly with your ideal consumers!
  • We learn the behavior of your consumers so you’re aware when they buy, how they buy and what medium best motivates them to buy.
  • We identify contexts for advertising, where your ideal customers spend their time, and identify the best manner to engage with them.
  • We profile and locate every single person online who match your ideal customer and invite them into your brand circle to expand your brand community.
  • Identify and connect directly to influencers who can create buzz and extend your offering to a larger audience.
  • We closely follow your competition and identify how they are ahead of you in business across social networks, forums and media. We share key insights with you, along with business opportunities for growth.
  • Develop demographic and psychographic information on your consumers to learn how to speak with your leads to ensure they convert.



AUDIENSE (SOCIAL BRO):  This is a Twitter and Instagram audience intelligence tool. The tool also offers a way to listen to everything a specific group of people has said since their entry to the Internet. The tool is a “gateway” into audiences and needs appending in PeoplePattern and PIPL to be more completely. Audience offers a unique and powerful dashboard for quickly assembling an audience related to a set of attributes, locations and even personality (Watson API is hooked up to Audiense).  A primary value of Audiense is: the quick development of large lists of Twitter handles related to how people self-describe in their Twitter bios. A secondary value is the ability to listen to everything these same handles have posted in Twitter since their presence on the platform. This combo is important as a way into an audience talking about a topic. It is also important as a means to interrogating a specific group about any other topics they talk about.

Audiense helps us answer the following questions:

  1. How many people are out there who self-describe as our ideal consumer?
  2. Where do these people live?
  3. What is our consumer talking about, besides our specific product, category or us as a brand?
  4. Who lives in our region that we can sell to?
  5. Who are the real people that talked about our category, competitor, product, and/or brand?


PEOPLEPATTERN: This is a relatively new entrant to the field founded by Ken Cho (founder of Spredfast). Ken has built a powerful engine for analyzing both conversations and bios from all social platforms. The tool also offers an impressive breadth of personas (both internally conceived and customized). These personas are populated with comprehensive insights on location, hashtags, interests, mentions, media, and many other attributes. The tool is in beta and is being used by a handful of agencies and brands now. The tool was conceived by Ken Cho and the storied technologist Jason Baldridge (  ). The tool is very specific, fast and deep, pulling up every bio and individual related to searches in People Pattern’s complex dashboard. One can also upload a CSV of social handles from most platforms and gain deeper insight into the individuals uploaded, along with full insight into what these people talk about. Primary values of PeoplePattern include the development of persona types and look-a-like audiences. A secondary value is the append of additional information related to individuals Twitter and Instagram handles. A third value is the ability to compare audiences side-by-side. Finally, the PeoplePattern tool is a convenient way to discover Twitter and Instagram handles of individuals/entities who talk about a subject in Twitter and Instagram. This is important because personas are a way to discover look-a-like audiences. The validation of these look-a-like audiences within PeoplePattern is exceptional. In addition, the depth of information about each persona type is truly exceptional.


PeoplePattern helps us answer the following questions:

  1. Who loves our category?
  2. Who loves our brand?
  3. Who is our critic?
  4. Who is our ally?
  5. What does the audience for our competitor look like?
  6. Who are the actual real people who are passionate about our category?
  7. Where do these people live?
  8. What persona types are passionate about our category?
  9. What other interests do our consumers have?
  10. What do lovers of our products talk about?
  11. Who is influencing the people who love our products?
  12. What media outlets should we use to reach our consumer?
  13. Who should we talk to about our product?


AFFINIO: This is an audience intelligence platform that uniquely identifies and groups individuals related to a query or uploaded CSV or social account. The tool is elegant in the way it creates nexus points of these persona groups/individuals AND major brands/themes/interests. There are unique tabs in the Affinio dashboard that give the user quick insight into potential collaborations with brands, micro-influencers or just a group of like-minded individuals “down the street”. The platform captures global data and is expanding beyond Twitter at this time to capture Instagram and other social channels. Affinio offers significant value to brand stakeholders who want to understand groups of real people talking about competitors and brand-relevant topics. Affinio also offers value related to discovery of real people for insights analysts to study and develop a POV related to any topic or theme. A primary value of Affinio: is the nexus of individual members of a report and interests. In particular, the segmentation of interests within Affinio is excellent.


AFFINIO helps us answer the following questions:

  1. What brands and interests do our consumer talk about?
  2. Who is influencing our consumer?
  3. Who is influencing our competitor’s consumer?
  4. What persona types do our consumers fall into?
  5. What content is influencing our consumer and our competitor’s consumer?
  6. What persona types should we be targeting in our campaigns?

The value of Spotright is that we gain an insight into the Buying Styles and Purchasing Habits of a specific set of Twitter handles. In addition, we gain insight into nexus points of brands, interests and any custom classifier with these same Twitter handles. There are other demographic insights within the Spotright solution that come from the deep Axciom and Epsilon sourcing by the original Spotright team – JP Lind (Epsilon and DoubleClick background) and Ed Messman (HiveLive, RightNow and KBM Group background). Access to the entire Full Contact data set was purchased early on in the history of Spotright, which allows for an exceptionally fast append process.


FULL CONTACT API:  A primary value of the Premium Person Enrichment Sheet in Full Contact and/or the API itself is: the append of other social handles, bios and data on individuals discovered within PeoplePattern and Audiense. When Facebook data was more open, the append of Facebook handles to Twitter and Instagram handles was a truly glorious experience. Even now, due to the archive within Full Contact, we do get a wonderful append of the Facebook handles, along with other social channels. This append is important because we can then find Facebook Groups and conversations (using Facebook Graph API) related to these same individuals discovered in another platform.


DATA MINING IN FB & LINKEDIN: The value in using a data mining solution to scrape individuals who self-describe as our target is very useful. In addition, the scraping of specific groups of individuals related to events, interests and locations is also useful. Finally, if a very deep recipe is written, a best-in-class data mining tool will open individual Facebook profiles and scrape a great deal of information, including what these individuals talk about. When one then takes these Facebook IDs and appends additional information in the tools described above, the size and specificity of an audience increases.


BRANDWATCH: This is a conversation analysis tool and now, as of Vizia2, a business process management tool. The audience tool within BW is still in development and is not as good as Audiense and PeoplePattern. Brandwatch is the world’s best source for public conversation data in 48 languages. The tool offers: complex boolean queries, customizable dashboards per business problem, full global coverage of 48 languages, along with brand specific dashboards, channel analytics dashboards and many other customized dashboards to overly the discovered mentions. It is also possible to perform non-language specific queries so that all mentions of a brand in all 48 languages show up in one’s dashboard. The tool has a scaled pricing model based on number of mentions and/or number of queries. There are literally thousands of case studies, resources, brand examples and agency examples to be found online for Brandwatch. The tool is the choice for the largest and best research agencies, including Ipsos, WPP (Kantar, JWT Intelligence, Ogilvy, etc.) and is the most used platform for conversation analysis by major brands. The team at Brandwatch is constantly innovating and includes access to scores of foreign language analysts for a truly global reach.



  1. I run a search in Affinio, PeoplePattern and Audiense using keywords OR by uploading a CSV of authors discovered in Audiense, PeoplePattern, BW (Brandwatch) and/or CH (Crimson Hexagon). I mix the tools and verify in this way.
  2. I wait for 2 hours for this search in Affinio/PeoplePattern/Audiense to populate
  3. I export the following sheets from Affinio within the Actions tab: Members, Interests, Bio Keywords, Locations, Domains, Hashtags, @Mentions, Topics. From PeoplePattern, I export specific audience segments, based on persona type, city, interests and other filters. From Audiense, I export specific audience segments based upon Real Avatar, Country, URL in bio, level of influence, time since last tweet.
  4. I create tabs within a single sheet with the above sheets.
  5. NOTE 1: (In some cases the Clusters from Affinio are unhelpful because I have to export from all Clusters and then I have to stitch the Social Handle columns from different Clusters together and then I have to upload to Audiense and PeoplePattern to get more specificity.)
  6. I upload the social handles from the Members tab in Affinio to Audiense and PeoplePattern.
  7. I export from Audiense and PeoplePattern and clean up.
  8. I stitch the Members (Affinio), Audiense and PeoplePattern sheets together in Excel.
  9. I clean up and put this fully appended sheet (using data from all three tools) into the first tab of the final document. (Remember, the other tabs have Interest Nexus from Affinio, words in bio from Affinio and Location data from all three in a fourth tab.
  10. I perform PIPL append on the names and links in the first tab.
  11. I stitch PIPL results (emails, phones, addresses) into that first tab in the last three columns.
  12. I perform queries in Brandwatch and stitch mentions into that first tab, next to Authors who have talked about category, brand or competitor relevant topics.
  13. I perform Author Group Monitoring within Audiense and stitch in Insights to the first tab.
  14. I perform Full Contact Person Enrichment to gain add’l social handles and add’l bios (verifying what PIPL gave me).
  15. I create code frames by hand and note insights while doing so. This is a separate process and gives us a powerful view into the conversation related to a category, brand, competitor or relevant topics to a business process. Export mentions from Brandwatch, delete duplicates, column titled Topic next to the Snippet, column titled Summary next to Topic. Code for percentage of (Human driven)
  16. I create a single page PDF with top line insights on the discovered individuals.
  17. I add Appendices to this single page PDF with supporting evidence for the Insights page(s). The Appendices are numbered and matched to each Insight.
  18. The final product is the Insights PDF, Insights Appendices PDF, and supporting spreadsheets. If the client is well-heeled enough, they get a branded dashboard that is “client facing” from BW and/or CH.
  19. Human analyst review and validation. (Human driven)


Relationship and Experience Marketing Plan

SUMMARY: The central themes of this document are relationship and experience. It is the express opinion of the author that SEO and advertising are broken models in need of transformation. The way to create awareness in today’s world is through relationships and experiences. Enterprises should consider focusing solely on creating the right relationships and creating experiences in the context of these relationships.

HOW TO DO THIS: The sequence of steps related to this method of going to market are as follows. Note that this is a summary document related to a master document filled with actual personas, suggested content and suggested experiences.

1. Identify the ideal willing prospect as related to your brand. This means that you write out on paper who this person is. Ideally, these people are micro-influencers, with regional popularity and super-engaged networks. Action: write out and refine over time this profile. As your community grows, you will notice the various strata of your desired types, from beginner to elite. Be inclusive to this spectrum and become THE experts in how one traverses from beginner to expert.

2. Use social network analysis tools, such as Brandwatch, PeoplePattern, Musefind and Audiense to aggregate large groups of these prospects. Understand more about these prospects using psychological technologies similar to CrystalKnows and Watson (IBM). Such solutions will give you lists of people (along with detailed bio info) exactly similar to your ideal willing prospect. You will also discover the content these people are posting, the events they are attending and the experiences they are having. Absorb this on a daily basis. The value of this intelligence is that you will have inspiration for content, for events to attend, and for experiences to participate in (and feature). Your community is found using these tools.

3. Employ humans (flesh and blood) to reach out to these prospects and meet with them in person. Invest your dollars in outgoing, intelligent flesh, who love connecting online and offline. Ideally, these humans you pay are also your ideal types themselves. Again, invest your dollars in charismatic, intelligent humans vs. outdated SEO and advertising approaches. The former is a love affair and gains you access to real dynamic community. The latter is a shotgun shot into the dark and is temporary, requiring increased investment for less reliable results.

4. Plan on a 12 month program (at minimum) of getting to know the community you found using the network analysis tools.

5. Plan on investing in content that follows the Content Grid approach from Jess3 and Eloqua.

6. Create content pieces for every stage along the consumer journey described in the Content Grid. Invest in research where you discover the best contexts for placing and socializing this content. Increasingly involve your community in creating this content with you, through their stories, quotes and experiences.

7. Plan on running campaigns that award specific, meaningful items from strategic partners, such as plane tickets for two to anywhere, to members of your community. Show your growing community that you understand them through what you award them. Be a giving brand. Plan on becoming known as THE place to make one’s adventure happen.Through your brand, consumers realized their adventure.

Social Intelligence of The Future — Focus on shortening the distance between the consumer and the brand

These are questions that we can be answering using insights from social data.

What can social data tell us about our consumer’s actions? What is he/she doing on a daily and hourly basis?

What experiences are our consumers having?

When our consumer turns away from a major brand, what is he/she turning towards?

What is our consumer experimenting with? Can we experiment with him/her?

How can we help our consumer as he/she faces so many choices?

How can we help our consumer determine what sources of information are valid?

Are we discovered in the midst, even at the core, of our consumer’s trusted sources of information? (influencers)

What does it mean to be seen as a basic utility by our consumer?

What does it mean to be the answer to our consumer’s “short term” needs/decisions/desires?

How can we help our consumer with small actions on an every day basis?

How can we be more pragmatic vs ideological as a brand? How can we be the answer for our consumer’s pragmatic questions and needs?

How can we help our consumer as he/she evaluates and re-evaluates his/her decisions about the smallest things? Where can we appear during that consideration phase?

How can we be there when our consumer acts impulsively? Where and when does he/she act impulsively?

How does our consumer’s “operating system” work? How can we “hack” or “patch” into his/her operating system?

How can we create activity that fits within our customer’s existing behavior (based on lots of small data points)?

A Network Analysis Process

A Network Analysis Process:

1. Subscribe to a social media monitoring service with a very hefty set of data (i.e.- Brandwatch)

2. Create an accurate query within this monitoring solution related to your marketplace. Date this query back 24 months. The goal with this step is to discover the largest networks (pages, groups, authors) related to a marketplace.

3. Go to the Export function within the monitoring solution and export the entire data set related to your 24 month query. Every row.

4. Isolate ONLY the Twitter results in an Excel document. In addition, isolate ONLY the Facebook results (in Excel).

5. Subscribe to Full Contact API ( ) at the highest level you can afford.

6. Download the Full Contact Person Enrichment Template (FCPET) from Full Contact API.

7. Set the Seed at 3 or above (in the FCPET document). Set the source to either Twitter Handle or Facebook ID.

8. Ensure you have a rock solid Internet connection.

9. Paste all Twitter handles from the data export into the first column of the FCPET document. Run the append.

10. Paste all FB handles from the data export into the first column of a second fresh FCPET document. Run the append.

11. Keep the results in the FCPET in exact order from the Brandwatch data export. This is so you can paste in a few columns from the Brandwatch export, such as sample mentions, account type (Individual or Organization), gender, etc.

12. Hire an analyst to meticulously go over the resulting spreadsheets and clean out the junk and spam authors. Use other tools, such as Melissa Data ( ) and Intelius ( ) to append more data in additional columns.

13. Organize by Impact score (Brandwatch) or by Region or by any other criteria important to you (use the Data sort function in Excel to do this).

You can use the final sheet to plan content-marketing, derive insights on markets, and understand competitor activity. You can also determine the “real people” talking about your brand using this approach.