competitive intelligence

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.

 

THE LINKEDIN LEAD-BUILDER MACHINE v1.0

The machine searches an Interest within LinkedIn. The machine discovers the largest locked group within this Interest group and gains access. The machine segments the members of this group by nation. The machine then creates a spreadsheet with Name, Bio, Email, Phone, Location, Company URL, Social Link 1, Social Link 2. The machine fills the name from individual LinkedIn profiles using the semi-automated functionality of LeadGrabber Pro. The machine fills the Bio from the brief description underneath the name in LinkedIn. The machine identifies the Company URL from the current place of employment of the individual. The machine uses eMail Verifier to match the Company URL with the name on the LinkedIn profile in various iterations until eMail Verifier states “Address is Valid”. The machine pulls the company phone number from the Contact page at the Company URL. The machine pulls the individual’s public LinkedIn profile. The machine searches within the Contact Info in LinkedIn for other URLs and social links associated with the individual. The machine then places a social link or URL in the Social Link 2 column.

Replacing email blasts with relationship marketing

No, it was the other guy, the guy who bought what worked, the one in charge of the real budget–he wasn’t easy, but he was worth it… ~Seth Godin

THE CURRENT SITUATION: Ever receive an email with a sales pitch? We all do. And what do you do with 90% of these? You do not have time to read them and you trash them. Many times even when the pitch is about something you really want or need. There just isn’t time to open that email and read the pitch, click on the link and do all the digital “paperwork” to get what you want.

Receiving an email blast from a company is different than receiving a helpful solution in the context of a comment thread in social networks. The former is likely to end up in the junk folder. The latter is “in context” and will be read every time. This is why corporations are ceasing email blast campaigns and building relationship marketing teams. This is why corporations are building customized communities based on customer needs and competitors’ shortcomings.

Eleftherios Hatziiannou writes, “Marketers spent fortunes every year for marketing research and data to understand precisely who their target group is, what they want and where they can reach them. Today people publicly say what they want by using social media. Wouldn`t it make sense to learn how to participate in this new kind of marketplace and thereby turn conversations into commerce?” (SOURCE: http://www.peopleizers.com)

THE DEEPER REALITY WITHIN CORPORATIONS: An organization that moves away from email to internal communications networks, such as Salesforce Chatter, Yammer or Sharepoint is an organization that gets the value of relationship marketing. In addition, such an organization gets the value of knowing the context in which an employee/customer is complaining.

Brian Solis, Principal Analyst at Altimeter Group, writes, “Collaboration takes more than the idea of Facebook behind a firewall. This is about aligning people around a common vision, to encourage engagement beyond the teams you know, to create inside and outside experiences that matter to employees, customers, and partners. Enterprise social networks represent the technology to bring your vision to life as they are merely tools that mimic the way that people connect and communicate in the real world.” (SOURCE: What’s the Future of Business – http://www.wtfbusiness.com)

It’s one thing to have an email, a name and a role in our marketing database. And then to blast a prescribed formula to segmented lists. It’s a far deeper action to have a complaint, a context AND an email, name and role. When an organization has EVERY complaint out there about a competitor/themselves PLUS the current contact info for those who are complaining, they have an opportunity to engage in conversations with those complainers one-to-one. This is called relationship marketing.

“We created a contextual social space where people interested by a topic (in this case the World Economic Forum – http://weflive.com/kpmg) could follow what what said about it and the brand was opening a discussion channel in this precise context,” writes Nicolas Dengler of Shore.li, http://www.shore.li

The question is whether they will use such information in a way that the customer truly gets and wants to respond to. Will they mobilize their marketing team to offer solutions one-to-one in social comment threads? Or will they simply do another email blast?

Ted Rubin, a world expert in relationship marketing, writes, “Creating the opportunity for customers to share via a social platform allows people to give feedback/suggestions real-time and therefore increases the brand benefit exponentially.” (SOURCE: http://www.tedrubin.com/blog/)

When asked about the difference between corporations running email blasts and those running Relationship Marketing campaigns, Giles Palmer, CEO of Brandwatch, the world’s premier social media monitoring service, said, “The answer’s obvious, isn’t it? The difference between email marketing and relationship marketing reminds me of a guy driving a car around a town centre with a big microphone screaming their message out versus someone walking through the crowd shaking people’s hands and talking WITH them. If the broadcast message is funny or informative, ok, it’s a way to get to a large number of people quickly. But if it’s not, it’s just noise. And who wants to be remembered as the noisy guy in the room.” (SOURCE: Personal call with Giles Palmer of Brandwatch, April 2013)

This transition from email blasts to relationship marketing IS the future of marketing and sales. And it is the next step in moving from a culture that looks at people as digits TO a culture that sees people as people.

SOLUTIONS:
Solutions for corporations to build relationship include (in order):

a) an audit of all complaints/feedback about a product/service (using listening tech, such as Social Media Monitoring tools),
b) a creation of responses internally and/or with the help of a content-marketing agency,
c) the assignment of an individual/team to respond within 24 hours to complaints/feedback in ALL social streams and comment feeds,
d) the creation of a “living” database where these responses and the resulting sales are documented.

PURPOSE OF SOLUTIONS:

1) To identify who is complaining about our competitor.
2) To offer solutions to these people directly.
3) To improve our products/services through knowing their complaints.
4) To increase awareness of our comprehensive understanding of this market niche AND of what our customer needs.
5) To increase sales.

IN BRIEF: Social prospects are developed THROUGH providing solutions in social comment feeds. Conversion occurs when a prospect finds the solution satisfactory AND better than a competitor’s solution. The process involves: identification of needs through listening, providing better solutions to these needs than competitors, follow up with people who want to use the better solution.

RESOURCES FOR FURTHER STUDY:

1. THE ULTIMATE EMAIL STATS LIST VIA HUBSSPOT:
http://blog.hubspot.com/blog/tabid/6307/bid/33901/The-Ultimate-List-of-2012-Email-Marketing-Stats.aspx

2. THE GRAND GUIDE TO SOCIAL SELLING VIA ELOQUA:
http://www.slideshare.net/Eloqua/the-grande-guide-to-social-selling

3: HOW TO DO RESEARCH IN SOCIAL NETWORKS VIA BRANDWATCH:
http://www.brandwatch.com/knowledge-base/ebooks/

Useful questions related to assembling social intelligence reports

a. WHO are the influencers around our topic? Who do we recommend as brand ambassadors and community managers from our findings? WHY do we recommend these individuals?
b. WHERE is our tribe, our customer in the social properties, blogs and major web communities?
c. WHAT VOLUME of conversation is there around our target keywords? Where are those large volumes of conversation taking place?
d. What is the SEASONALITY of conversation around our topics of interest?
e. What TIME OF DAY do people discuss our topics of interest?
f. Which LINKS and SPECIFIC CONTENT are people sending to one another related to our topics of interest?
g. In which CONTEXT are the ‘keywords’ of interest used?
h. Which CLUSTERS OF CONVERSATIONS tend to gather the most interest, volume of attention and influence?
i. Which clusters of conversation are most important to our MARKETING campaign’s needs? REPUTATION of a brand? PRODUCT DEVELOPMENT?
j. Which TOOLS proved most effective in our social media property research? Were there differences in our findings from the different tools? What account can we make for these differences?
k. Which METHODS OF VISUALIZATION are most effective in getting the message across to our client?
l. What INSIGHTS are MOST helpful to our client?
m. What can we find on ALL of the above about our competitors?