Listen to your customers, advises Christopher Penn, Co-Founder and Chief Data Scientist at TrustInsights.ai

Media 7 | November 16, 2021

Christopher Penn, Co-Founder and Chief Data Scientist at TrustInsights.ai shared his insights with us on how marketers can make better use of data, attribution models and natural language processing to promote conversions and increase customer engagement. Read on to find out about his three-part strategy for successful marketing campaigns.

Data of any kind is a value exchange trade. I give you my data, you give me something in value in return.

MEDIA 7: Hi, Christopher, thank you for your time! We are very excited to have you here! Let us begin with you telling us a little bit about TrustInsights.ai and what has the journey been like. What inspired you to co-found Trust Insights?
CHRISTOPHER PENN:
My partner and I worked together at a public relations firm for a few years before founding the company and a lot of our work was focused on change management and governance, analytics, data science, machine learning, and AI. The firm we were at was moving in a different direction. So that combined with a few other factors made us think it's probably time for us to go off on our own and do something that was aligned with our focus. That is the genesis of the company. We were trying to see if there was a large market for the types of marketing, technology, and management consulting that we wanted to do. And so far, so good! We are three years into our journey and certainly having a lot of fun. We have a decent amount of revenue. We are still only three people, but the power of automation and AI and data science makes that scale well.


M7: That is very inspiring! To be honest, I think it is part of every one of us. At some point, we want to get off and start on our own. So you've also mentioned that you are a minority and women-owned business - could you please tell us a little bit about that? How is the journey been like so far?
CP:
So, yes, it's funny - by law and our company charters, we're 50 - 50 partners. My partner identifies as female. I am a non-majority in the USA and so we meet the criteria for both of us. We've seen and experienced more issues with the gender stuff than with anything around the race. When we were planning the company, we had thought initially, maybe we should try to go get some funding, try and get some investment. We decided that Katie, my partner, was going to be the CEO because she is better at the overall operations and the running of an organization. She is a better people manager and things like that. I am more of the mad scientist who's just going to sit in the lab in the back and just make crazy things and make stuff blow up. Having worked together for three years before founding the company, I knew that she was the better manager, the better executive, better at running an entity than I ever would be. Very early on when talking to some of those investors - we had one investor say to our faces that they will not fund a company that is run by a woman. Like well, all right, we will scratch you off our list of people we ever want to talk to again, because that attitude was an attitude that was common 75 years ago. However, in 2018, in the modern world that just does not fly anymore.

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M7: As data and machine learning have been a powerful influence in the marketing industry, at Trust Insights, what are the most powerful data science and machine learning-powered solutions do you offer to your clients?
CP:
Probably the one that is the most in-demand are things like attribution models. So we have the custom code that we've written for getting data out of Google Analytics to look at to build an attribution model. It's based on alignment with how we think attribution works. It's all different from the way Google does theirs, Google has published papers about how theirs works, and theirs make sense of what they're trying to do. It's aligned with their goals and by no means bad technology. If, for example, Google were to use our methodology, it wouldn't scale as well. It's much more computationally intensive. And so it's fine for a consulting firm to reach, run a model on behalf of a client, get set up and go and do its thing, get a sandwich or whatever, and come back in 20 minutes and it's done. If you have an application like Google Analytics, you can't tell users - oh yeah come back in 20 minutes, and click on this button. That's not a good user experience. So we have a good channel level attribution. And then we have content level attribution where we look at what are the places people go to on your website, on your digital properties and what are the paths to conversion?

One of the most commonly walked paths, the pages and the content that most commonly nudge people towards conversion, either in general or they have very high - what we call - conversion efficiency, meaning that if there's a Page A and Page B and Page A requires three visitors to convert, and Page B requires 200, where should I send my traffic to? Let us send it to Page A because it's a more efficient page for conversion. So in terms of machine learning stuff, that's some of the basics that we do that are very effective. Then we have been doing a lot with natural language processing, particularly anything around customer experience. Therefore, a fun example of a recruiting company - a couple of years ago, they hired us to answer the question, why are our job ads not performing. Why are we spending a lot of money and not getting many candidates. Therefore, we took 5000 of the ads and did some natural language processing on them, trying to understand the words and phrases that were being used in these ads and how prominent they were, and then they gave us access to their call center.

We took 17,000 calls from their call centre, converted them into text using just AI-based transcription. What we found was what the candidates were talking about in these calls - starting pay, pay per mile, home on the holidays, what kinds of truckloads am I hauling. None of that was in the job ads. So we said - if you change the language you use in the ads, you will attract more candidates. They did and they saw a 40% increase in conversions within 30 days just by changing the language that they use. That's an example of the natural language processing aspects that you can do that are just so impactful because companies have all this data that's unstructured that they're not using. It just sits in an inbox. It sits in a call center, and nobody ever digs through it to use for marketing purposes.


An important thing about attribution that a lot of people forget is that it is not just an analysis of your marketing efforts, but also a mark of the channels’ effectiveness as well.



M7: That's true. So given that data is so important today, how do you think the marketing industry is changing? What are the latest trends in the marketing industry and how do marketers today need to adapt to these latest trends?
CP:
There's a bunch of trends, the first one, and I think the one that's the most important is that marketers got spoiled on the level of data and access they were able to get, particularly from the third party. So third-party data in the last five years or so, markets have seen a massive amount of data gathered by big companies like Facebook and stuff like that. And now, in the last two years, we have seen legislative efforts. Because GDPR took effect in 2018; CCPA took effect in 2020; CPRA is taking effect in 2023, and PPIL takes effect in one month from today in November that covers the entirety of the People's Republic of China, which is the largest market on the planet - all these laws are intended to curtail the use of information that consumers did not give consent for. So marketers very quickly need to figure out if they haven't already, how they can obtain informed consent for the data they're gathering. If they want to continue gathering that data and to understand that they do not have a right or a privilege to customer data, they have to earn it. Data of any kind is a value exchange trade. I give you my data, you give me something in value in return.

Consumers are aware - B2B and B2C doesn't matter - consumers know that the moment they fill the form that there will be a salesperson calling, there will be 44 emails in the inbox and they are not going to stop stalking them and they are going to see this ad all the time. As a result, consumers say that they don't particularly like that as an experience. They have legislated in places and then you have technologies that are doing the best. I feel saddest but some 30% of people use adblockers of some kind. Apple just released the blocking of third-party cookies on various devices - the new mail privacy protection which 15% consumers do so far and 96% of consumers opted for blocking app tracking in IOS 14 and the new hide my email feature in which creators create a burner email address in your iPhone in your mails is fantastic. So, all these tools exist now for the consumers, to withdraw consent from marketers - to say that you need to provide me more value and if you don't I am not going to be giving you the things that you want.

The next thing is that the pandemic, as everybody knows, accelerated digital transformation in the sense that we have been sitting at home for 18 months and these devices have become our lifelines to other people and so a lot of companies again don’t know this experience, as in how people communicate and companies have not figured it out and are far behind. But, it also means that how people are connecting and communicating is different, and how people use different communications networks now. Facebook itself has lost a lot of traction especially among people under 30 to large networks like Snapchat and TikTok and stuff like that, but also to private social communities and these are popping up like weeds everywhere. So the two platforms that people find the best are Slack and Discord. Discord has taken off like a rocket in the last 18 months. There are servers out there for literally every conceivable thing, many of which you can't talk about in a professional setting. They are out there and that's how people communicate at their invisible ad target. They are invisible to marketers, and to search engines. So we have all those conversations happening, same with text messaging and all the secure messaging apps. Signal and Telegram – that is there where conversations happen, conversations which marketers wish they were part of but they are not. So marketers have to figure out how do we get invited into these conversations; how can we find actual fans and advocates of the brands of our company that will be willing to ambassador us into private communities to introduce us as marketers so that we can even just see what is going on; hear what is being said and again, and there are not many marketers doing that.

They are very far behind the curve and this trend always continues to increase because for a lot of people and a large number of people under the age of 30 don't want companies tracking them. They don't want things happening without their consent. I talked to my 16 year old child, who uses Firefox because of its ad-blocking technology and has something like 14 different email addresses. They have just one for corporations and they have a rule set up that sees an email and it automatically gets deleted after an hour because they are like I don't ever want to hear from a corporation. I just needed to sign up for something. So, as marketers, we have to do two things - we have to understand the changes which are happening and we have to listen to people more and we are not doing either one of those things very well.

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M7: So what will you say is the benchmark of a successful marketing and sales strategy today - we are talking about a time where email marketing and even newsletters are now almost something people consume and are in demand - so what according to you are some of the benchmarks of a successful marketing strategy? How should a marketer approach?
CP:
You have success in three areas and I evaluate them based on the top, middle and bottom of your marketing operations. On the top is awareness - attention is everything at the top of the funnel because if you don't have people's attention you have nothing else. A lot of people like to go with brands and stuff like that but guess what, if nobody remembers who you are then there is no rest of your funnel. If the top of the funnel is empty, there is no rest of the funnel - that is number 1.

Number 2 is, when it comes to engagement and retention of that attention, publishing and again there are so many different options - there are email users who have made a huge resurgence in the last few years. When you see something like Facebook and the way Facebook behaves, sometimes you feel that you don't want to do business with a company that behaves like that. If you look at the way Google operates, it is very effective but also extremely expensive. Things like email are an intricate part of keeping yourself in front of an audience and if you can figure how to provide a publisher with a lot of value then you grow an audience that you get to hold on to for a substantial time.

In the last three years, my mailing list has gone from 40,000 subscribers to 250,000, because people want stuff in their terms. When I send someone an email it can stay in their inbox for as long as they want it. They don't have to read it when it comes out they don't have to be like - if you look in your social media feed if you don't interact with that post right now you won't find it again because all these different algorithms kind of change what you view - you don't have those issues with email. It is there when you need it to be and they are on your schedule and your preferences and its on-demand publishing. Videos are the same thing, some companies are doing very well and people doing very well with stuff like YouTube. Not because YouTube is inherently better as a channel but simply because it's there when people want it. There are a lot of people who have looked into live streaming and live social audio and stuff like that and that's fun but ultimately most people don't do scheduled appointment media. They do what they want to. Netflix has trained us to have whatever we want and whoever we want and marketers have to adapt to that.

The third part of that strategy is your community. So if you do not have some kind of a community that you can occasionally pitch to it but for the most part it is about benefitting the community and using your responsibility to be a student of that community. Otherwise, you won't be able to hold on to them. More importantly, use the presence of mind when they need it. So we have a Slack group and you can see about 2000 people. It's a community that we created and run and administer and nurture. Most of the time we are not pitching ourselves. Most of the time we are answering questions and people talking to each other. It is a way for us to keep those true fans, if you will, in connection with each other and in a form that we have a little bit more control over. There is no algorithm in a slack group - you see what you see.

So you have a three-part strategy - awareness, publishing for retention, and community, and that is a successful strategy. There is a study done by LinkedIn, either in the LinkedIn labs or LinkedIn institute - one of the two. It was looking specifically to B2B but it applies to a lot of cases for any kind of complex sale and it states that 95%-98% of the audience is not looking to buy. So if all your efforts are saying buy now, at best, you are going to get 2% of your audience and going to piss off the rest. If you create the strategy of awareness and publishing and community and you think about a person and they have the attention spotlight of that of 2 seconds - it is looking around for a solution. If you have their attention, you can earn that business in that very thin slice of time. The rest of the time you provide value so when that spotlight comes around again you are there and that's the strategy that you were pursuing. That is seeing a lot of companies for a successful pursuit.


M7: What are the different ways that TrustInsights helps the clients achieve a funnel, a strategy exactly the way you just explained it?
CP:
So a lot of it is providing with data and analytics so that they can make better decisions for example with awareness. Companies will ask - how do we put together a marketing strategy or a marketing plan or particularly a content marketing plan and using things like predictive analytics, times used to forecast. We can take a keyword list for example out of your SEO tool and forecast forward the probability of that of when each queue will be most searched in the next 52 weeks and then week by week we find topics or phrases people be searching for that week. Then you must change your content strategy to reflect what people are thinking about and when they are thinking about. You will do better because there is nothing quite like a potential customer thinking about say analytics, Google analytics for example, and that week in their inbox they get a newsletter with a lead article and go, “Oh I was just thinking about that!” So predictive analysis depending on the topic can be a very strong solution for not only being real with the customers but understanding what they want, but when they want it too.

The second is analytics infrastructure. If you don't know what you have and can’t measure, you won't be able to manage it. You can’t manage what you can't measure. A lot of our clients when they first come to us don't have the right pieces in the right place. It is kind of like a kitchen where all the appliances are taken in parts and spread on all counters. Technically, they have everything, but it is not put together right and they don't know how to use them. Maybe they have this nice new piece of marketing automation software but they don't know what to do with that thing. It is like having a nice blender and you are like, I should put the steak in this. No, that's not what it's for! So we do a lot of training and education for our clients. It's like you make soup with the blender, for the steak you use the frying pan, and things will work out a little bit better. Don't make soup in the frying pan! It's a horrible idea.

That's another key part of what we do for clients and then, of course, there is a lot of the changed management - helping a company change its process and train its people to be able to use the technology. If you have Google analytics and Google tech manager set up, you have world-class analytics capabilities. If you have set it up properly, it is a world-class tool but if you don't know what to do with that data and don't know how to make decisions from it, then it is like owning a nice tesla you never drive. It looks great near the driveway, but it is not fulfilling the function that it attended for. If you have Google analytics and you don't use it to make decisions, it is just a decoration. That's the third big thing - helping companies use the technology and data to make better decisions.

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If you don't know what you have and can’t measure, you won't be able to manage it. You can’t manage what you can't measure.


M7: Speaking about TrustInsights, you also have an AI-powered retribution modelling. Could you please tell us a bit about that?
CP:
Well yeah, that's the mark of chain modelling. So we are using the mark of chain propensity analysis for a channel-based attribution figure. An important thing about attribution that a lot of people forget is that it is not just an analysis of your marketing efforts but also a mark of channels’ effectiveness as well. We tend as marketers and certainly advertising companies that has tried to persuade us that everything is our responsibility but half of the responsibility is of the AdTech platform. If the AdTech platform has a terrible audience, it doesn't matter how good your ads are, you are going to get crap results out of it. So good attribution analysis can help you better understand the effect of all the different channels you are working with and then you can start to dig in and say - well, is this channel not working because we are bad at using it or is this channel not working because it is a bad channel?


M7: You have said before that it is very important for marketers to be aware of their customers and what they want and make their approach based on that so that they can convert them - how would you say, marketers today, should stay in touch and keep up with changing consumer demands?
CP:
That is an easy one - talk to your customers and listen to them when they talk to you. I am astonished at the number of companies who would do things like have three-day executive retreats on your bills. They will be in a room full of post-it notes with what the customer wants, and then when you listen to them you will know that not one of these people, in the last 18 months, have talked to a single customer. They have not listened to the customers and they have been guessing based on their own opinions about what the customer wants and their guesses, in a lot of cases, are wrong. One of the best examples of a company which did this well is T-Mobile and I use this example a lot because it was great in its simplicity. Under John Legere, for about 6 years, they did this marketing board. They went out and did a bunch of marketing research with their customers, talked to their customers, looked into their customer service inbox, listened to their call centre, and they made a long list of everything their customers hate.

Extra fees, absurd regulations of what people can trade-in and they were like - hey, let us make a list of all things that our customers hate and let us stop doing them one at a time. It was a brilliant strategy that allowed them to vacuum up a bunch of issues because they stopped doing things that customers hate. If you look in the marketplace of what all that’s different that your competitors do, and you listen to your customers, you talk to them, you pick up the phone or you go up for coffee - wear a mask - anything like that. Ask them what they don't like about our industry, why don't they like us, what they wish you could change, and you listen. You make a whole big set of long lists, you do some quantitative survey, and they say - let's stop doing the things that our customers hate the most. that are pretty easy in terms of marketing and sell it to the customer. It's like - hey you hate this, we are going to do this less. Now is that is great, not necessarily does the customer appreciate it. It always astonishes me, the length marketers will go to not talk to a customer - we want to stay in tune with our customers, and we will look at social media managers and research firms, but have you tried talking to the customers? Have you gone down to the call centre and just listened? Have you had lunch with your customers recently?

Companies that do that are very successful because they can say that this is what our customers want us to do. You know it’s funny when a lot of the latest product release from Apple with their new line of Macbooks, there are two things - the magnetic power charging, the one thing the people really like, so they brought that back; and nobody liked that touch bar, so that can go away and put our function keys back and everyone was like - this is amazing. If you have listened to the customers and stopped doing the things that they hate, they will like your products more.

ABOUT TRUST INSIGHTS

Trust Insights was founded in 2017 with a simple mission: to help marketers solve/achieve issues with collecting data and measuring their digital marketing efforts so that they can make better decisions with the data and exceed their goals with more automation, fewer errors, and deeper insights. They light up dark data. They help businesses make better decisions, faster. They make the world a better place by helping companies unlock and transform their data into useful analysis, valuable insights, and actionable strategies.

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Hightouch | January 30, 2023

Hightouch, the industry leader in data activation, announced the availability of the Personalization API, a low-latency API intended to customize any customer experience. The Personalization API enables any system, including internal and external SaaS applications, to get cloud warehouse data with a response time of fewer than 30 milliseconds. The feature integrates seamlessly with all prominent data warehouses and transactional SQL and NoSQL databases and supports any data structure (e.g., people, corporations, products). Now, all corporate users have access to client data in real time, whenever and wherever they need it. Modern customers want, if not expect, individualized experiences with every company interaction. A recent Forrester survey revealed that 68% of consumers prefer to return to an unsatisfactory website or business. However, according to a recent Gartner report, as many as 63% of digital marketers still need to grasp the promise of customization technologies. Hightouch's Personalization API solves this pain point. It makes it simple for any business team to use the modeled data in the warehouse and transform it into captivating real-time customer experiences. Businesses can handle a variety of new use cases using the personalization API, making it simpler than ever to create personalized client experiences, including: Delivering in-app or web personalization like article recommendations, customized search results, or nearest store locations to drive conversions Powering tailored marketing campaigns by enhancing marketing touchpoints with dynamic data points, such as product suggestions, through consumer interaction platforms Optimizing product testing by providing decision and experimentation systems with consumer information, such as audience inclusion or exclusion About Hightouch Hightouch is the premier platform for data activation powered by Reverse ETL. Integrate customer data from your warehouse with the technologies used by your business teams. From sales and marketing to support and customer success, all business teams want timely, accurate, and relevant customer data to give context to their current products. It makes your data actionable, whether boosting connections with clients through CRM, refining ad text, or customizing email. The company is based in San Francisco, CA, and is backed by top investors, including Amplify Partners, ICONIQ Growth, Bain Capital Ventures, and Y Combinator.

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BUSINESS INTELLIGENCE, BIG DATA MANAGEMENT, DATA SCIENCE

Daasity Launches ELT+ for Commerce, Powered by Snowflake

Daasity | February 01, 2023

On January 31, 2023, Daasity Inc. announced the launch of ELT+ for Commerce, powered by Snowflake. Customers will benefit from ELT+ for Commerce since it will allow consumer companies selling via eCommerce, Amazon, retail, and wholesale to deploy a complete or partial data and analytics stack. Building its solution on Snowflake has enabled Daasity to use Snowflake's unified, integrated platform to assist clients with data extraction, loading, transformation, analysis, and operationalization. With Daasity, companies can manage their whole data environment with a single platform that incorporates Snowflake. Daasity provides data-driven omnichannel consumer branding. The Daasity platform, created by analysts and engineers, serves the diverse data architecture, analytics, and reporting requirements of consumer companies selling via eCommerce, Amazon, retail, and wholesale. Teams throughout the organization can use Daasity to gain a consolidated and standardized view of all their data, independent of the tools in their tech stack or how their future data requirements may evolve. ELT stands for Extract, Load, and Transform, meaning that clients can extract data from multiple sources, load it into Snowflake, and transform it into actions that marketers can follow. Building on Snowflake allows product and engineering teams to create, expand, and manage their applications without incurring operating costs, allowing them to provide innovative solutions to their customers. Through the Powered by Snowflake program, developers have access to tools that assist them in designing, marketing, and operating Data Cloud apps. About Daasity Daasity, founded in 2017, is the first and only eCommerce analytics platform designed specifically for consumer goods businesses by market leaders. It centralizes a brand's data into a functioning data model so that it can evaluate and send its data to its primary marketing channels to get more value from the data. The adaptable modular data platform from Daasity enables businesses to discover insights from their data that enhance sales, optimize expenditures, and save expenses. Over 1,600 of the fastest-growing companies in the world rely on Daasity. It tailors a business intelligence solution to the unique requirements of consumer goods companies.

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