market research

Audience Intelligence Formula – Late 2017

SUMMARY: The formula for best-practice audience intelligence work is dynamic, due to rapidly advancing technologies and practices. We also have to take into consideration federal and nation-state regulations which are constantly in flux. As of December 2017, this is a formula for producing a fully enriched audience based on the beginning point of email, social handle, or a conversation snippet from social media, blogs, forums or comment threads on news sites. I might add that the acceleration of AI (Artificial Intelligence) and ML (Machine Learning) is rapidly condensing the steps below. APIs (Application Programming Interface) are being woven together to produce highly sophisticated machinery that blends outputs from various data sources.

 

THE FORMULA (LATE DECEMBER 2017):

STEP 1: Interview the client to determine goals and deliverables. This is important because we want to understand the client’s business and his specific goals related to the research. This is the time to see eye-to-eye with the client and really get to know his/her business from the inside-out.

 

STEP 2: Perform tests using the software below to discover opportunities related to the client’s desires/needs. Most social monitoring/aud intel solutions provide a way to quickly preview “the universe” related to a specific research request. This step is important as part of putting together the proposal for the client.

 

STEP 3: Design the audience intelligence study. Gain approval from the client, sign contracts, receive funding from the client. This is important because the client will want to look over the exact type of deliverable he/she will be receiving, as well as hearing a bit about your approach in putting together the final “data lake” of prospects and, of course, how the insights will be presented.

 

STEP 4: HOW DO PEOPLE DESCRIBE THEMSELVES IN SOCIAL BIOS: We gather a set of social handles where our keywords are in the bio. This from Audiense.com, Affinio, Brandwatch and PeoplePattern primarily, but can also be from using Data-Miner.io in LinkedIn, along with many other sources herein un-named. This is important because self-description by individuals is rather verbose these days..and this is helpful to us in finding our targets. And, where self-description is not verbose, there are clues through company/press/3rd-party descriptions of specific individuals who work for/play at/eat at/drink at/shop at/you-name-it at the locations/venues/places we are studying.

 

STEP 5: WHAT DO PEOPLE TALK ABOUT IN SOCIAL MEDIA/BLOGS/FORUMS: We gather a set of conversation snippets related to our keywords from Brandwatch, Sysomos, Crimson Hexagon and/or Meltwater. This is important because what someone says about an activity/product/service/location/you-name-it contributes towards our understanding of the consumer/customer/competitor’s consumer/customer. In addition, these conversation snippets from social media, forums, blogs, comment threads on news sites form a body of data that we can segment into specific topic groups. These specific topic groups can then be used to form a point of view/set of insights on the target we are studying.

 

STEP 6: SEGMENTING STEP BY MACHINE – TOPIC MODELING APPLIED TO BIOS & CONVERSATION SNIPPETS: We use Converseon’s Conversus tool to perform topic modeling and separate bios and conversation snippets into discreet topics. This is important because this speeds up the analysis of the bios and separates out the bios that matter to us the most. No solution in the world is more accurate and complete in segmenting bios and conversation snippets into discrete topic groups than Converseon’s Conversus. This solution is pure magic and the analysts at Converseon who are using Conversus are second-to-none in their expertise at building out superior insights based upon the use of their in-house solution. It is during this stage where an analyst begins to really gain deep insight into a sets of bios and sets of conversation snippets.

 

STEP 7: SEGMENTING STEP BY ANALYST:  Now, these analysts wade into the output from Converseon’s Conversus and identify the Topic where our targets are present (and any other discovered target – unknown unknowns). This vital step by humans helps us know which Topic groups in Conversus are populated by our target. This is important work that can be recursive, whereby the analyst segments the data using Conversus, reads through the results, and then segments again to refine even more deeply. I might add that this particular step is where the machine will eventually outstrip the analyst. That outstripping of the analyst will take some time to come along, though. For now, on this step, the human continues to be the last mile.

 

STEP 8: RE-STITCHING AFTER SEGMENTING STEPS: Reunify the bios from the “right” Topics in Conversus with the handles in the original source data sheet. This is important because we want to have the correct bio next the correct social handle. We also stitch handles and bios next to discovered conversation snippets at this stage. We find that working in Jupyter notebooks using Python is one of the handiest ways for our teams to work together efficiently on this step.

 

STEP 9: PEOLE PATTERN AUDIENCE INSIGHTS STEP: Upload Twitter AND/OR Instagram handles into PeoplePattern for deeper enrichment of Interests, Location, Age, Persona. This is important because we find out more about each person and we also delineate between Individuals and Organizations. In addition, we move a step closer through PeoplePattern to verifying the “real people”. Finally, we gain insight into the Persona types, Interest groups and lots of other useful info.

 

STEP 10: FULL CONTACT STEP: Use the Full Contact API to append add’l social handles. The value in this particular step is discovering a full name related to the handle AND additional social handles. We also gain bios from various social media handles, thus bulking out our story about an individual.

 

STEP 11: PIPL STEP: We use the PIPL API to gather Email, Phone, Address, other social handles, age, and many other bits of info on individuals. This is important because we will gain additional important information about the individuals that verifies they are “real people”.

 

STEP 12: CRYSTAL STEP: We use the Crystal Knows API to enrich the profiles with DISC personality type, personality overview, messaging guidance, selling guidance. This is important because then we are guiding our client on how best to market, advertise and sell to this individual. We can then group individuals by DISC type, if desired.

 

STEP 13: CLEAN UP ROWS FOR COMPLETION: Stitch together the results from the various APIs and then filter for complete rows. Again, we use Jupyter notebooks and Python for this work, as the teamwork and efficiency is vastly improved. This stage is important because we want every row to have every cell filled with correct & complete data.

 

STEP 14: EXACT DATA STEP: If we want to add an extra step for verification at this point, we run the Exact Data enrichment on the emails/names discovered. This is important because this extra step adds validity to the claim that our audience is full of “real people”.

 

STEP 15: SPOTRIGHT STEP: Upload the social handles into Spotright to gain enrichment of offline Axciom data, such as buying/purchasing styles, net worth, income level, political/religious affiliations, housing info, household complexion info, brand preferences of a specific group uploaded and much much more.

 

STEP 16: INSIGHTS, METHODOLOGIES & RECOMMENDATIONS PDF: Create 3-5 page Summary PDF with insights related to the research. This is important because brand leadership will now have a set of insights about the discovered individuals (our initial data lake of prospects) and, importantly, we can recommend further research steps for successive work together.

 

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 ( https://www.fullcontact.com/developer/ ) 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 ( http://www.melissadata.com/ ) and Intelius ( https://www.intelius.com/ ) 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.

Social Business Intelligence Advance #4

The business intelligence solution that marketers want is the following: a cloud-based service that is comprehensively analyzing in real-time networks of regular customers AND matching these customers (and their friends) to upcoming deals specific to past purchases. For instance, if Amazon were to fully integrate its data with Facebook’s data, a profound level of matching would become possible. Senior leadership within major FMCG and retail entities should be actively cultivating technical vendors and in-house technicians to achieve this type of customer intelligence solution.

Social Business Intelligence Advance #1 and #2

When social business intelligence solutions provide a “Create Prospects CRM” button, the social analytics industry will have leapt one more notch forward. What it looks like is this: a series of 10,000 individuals have commented on a specific brand/issue over 1 month AND this CRM button collects Name, Current Address, Current Phone, Current Email, Current social links for each individual. Instantly. Downloadable in a CSV format or a colorful PDF “dossier-style” format. The social media monitoring solution that offers this button will become a global leader in prospect generation.

Advance number two is when this service is fully applicable across global borders, delivering such info for residents of all nations.

The Sweet Spot in Social Business Intelligence for Weaving Marcoms and Sales: The Machine & Marketing/Sales Process

CONTEXT:
A fierce debate still rages between marketing and sales in most organizations as the enterprise seeks to understand how to use social data for both silos. With exceptional software and smart cross-silo relations, marketing and sales can collaborate on nurturing and closing ideal prospects. This blog post has outlined the type of software needed to do this AND a sample sales approach for teams to consider.

WHAT THIS POST COVERS
This post covers three specific topics:

1. The exact description of an ideal social business intelligence “machine” that would serve both marcoms and sales.

2. The functionality this social business intelligence machine would possess.

3. A set of potent actions that combine a bit of marketing and bit of sales, thus demonstrating how one can progress from market research (using social data) to a closed sales deal.

THE IDEAL SOCIAL BUSINESS INTELLIGENCE MACHINE: The sweet spot for social business software is between the marcoms & sales silos, between pools of potential fans & fresh prospect data. The social business software of tomorrow will bring understanding between marcoms and sales, will create an easy funnel for “smart” fans/followers to become customers. Deriving prospects from social data has never been easier with the combination of solutions now avail to the marcoms & sales silos. Now these solutions need to be “merged” into one single machine. I describe this machine below.

THE EXACT FUNCTIONS OF THE IDEAL SOCIAL BUSINESS INTELLIGENCE MACHINE (as desired by Marketing and Sales silos):
In the coming powerful social business intelligence software (the “ideal machine”), we will see the following features:

1. Dials to find the exact people fitting prospect profiles. Imagine being able to pull every profile from every major social network AND THEN have dials to hone results down to exactly the customer profiles your business seeks.

2. Get suggestions from the software (from “the machine”) of other “pools of prospects” and prospect types BASED UPON your initial search.

3. Then, imagine pushing a “button” and getting current phone, email, physical address, add’l social links appended on-the-fly to the social profiles discovered thus far in the process above.

4. Now, mix in Topics of Influence & Volume of activity by each profile relative to the themes in your marketing & sales campaigns.

A SET OF POTENT ACTIONS FOR MARKETING & SALES AFTER EXTRACTING IDEAL PROFILES FROM THE SBI MACHINE:

1. STUDY THE LAST FEW DAYS OF TWEETS/SOCIAL MESSAGING: See what the individual is talking about. What is important to him/her? Jot down one or two specific points about these tweets/social posts/forum comments that you can compliment him/her on.

2. STUDY THE WEBSITE OF THE INDIVIDUAL: See how the individual presents himself/herself to the world. Find one to two items on the website to compliment the person about. This will make the call warmer and open an opportunity to collaborate.

3. SEND AN EMAIL TO THE PROSPECT FIRST: A powerful way to invite the person is to send a personal email wherein you introduce yourself briefly, lace in the compliments you discovered through Twitter, other social properties, blog comments, and his/her website, and then invite the individual into a collaboration.

See below sample of an email to send:

Dear Tom,

I am a Client Partner at BrandX, an FMCG group based in Los Angeles, California. Your materials online and, in particular, your steady stream of tweets chronicling your typical business process have impressed me. Would you have some time during the coming week to discuss what you are up to, what we are doing, and a possible collaboration with us?

Kind regards,

Client Partner
BrandX

4. SCHEDULE A PHONE CALL: When you get a reply to your email, schedule a call with the person. The call will involve listening to the Prospect, letting him/her know what we appreciate about him/her, what we saw in his/her materials and then working on an idea to collaborate on. It is a good plan to come to the call with some options that are personalized.

SUMMARY:
A fierce debate still rages between marketing and sales in most organizations as the enterprise seeks to understand how to use social data for both silos. With exceptional software and smart cross-silo relations, marketing and sales can collaborate on nurturing and closing ideal prospects. This blog post has outlined the type of software needed to do this AND a sample sales approach for teams to consider.