Wednesday, November 13, 2019

 Digital Marketing Maturity Model

Would you say your company is leveraging at least 75% of the features and functionality that your martech stack provides? No? You’re not alone. Over the years I’ve noticed a pattern in adoption of digital marketing tools. Many companies get to a point where they’re using about 20% of the platform’s capabilities and then plateau. Why?

Reasons typically include:
·       Lack of skilled personnel to successfully guide maturity
·       Lack of time to focus on improvements
·       Process limitations that might prevent maturity
·       Data limitations/integrations that prevent maturity

Since digital marketing is typically a significant percentage of the Martech stack investment, it makes sense to work toward continual improvement, stretching, exploring and leveraging all the nooks and crannies digital platforms offer. But how? What should you focus on and how do you measure success?

To that end, I’ve created the following Digital MArketing Maturity model, which acts as a high-level GPS guide in quickly identifying where you currently are, what to focus on next and what success looks like at each stage. It is a compilation of existing maturity models, together with my own years of digital marketing consulting experience.

You’ll notice its broken down into 5 maturity levels, from Crawl all the way up to Best-in-Class, across 9 themes, including CX, Strategy, Targeting, Data, Analytics, Sales Alignment, Tech, People and Process.

It’s no accident that the very first theme is CX, since it is the end game and overarching cumulative goal of maturing the rest of the themes.

Where to Start

Obviously, there are many layers within each stage, but the best approach is to begin with a high-level assessment of where you are now, within each of the themes (columns). It’s important to get consensus on where you are now from all those who will ultimately contribute to marketing’s progression up the line. If the data team thinks you are at the RUN stage and you think you’re at the CRAWL stage, good luck making any progress. Misalignment is one reason companies get stuck in a stage to begin with.

Making Progress

It’s important to only focus on those activities that will pull you up to the next rung for any given theme. Don’t try and boil the ocean and go from crawl to BIC all at once. Take each rung one at a time. Once you’ve achieved it, focus on achieving the next rung, and so on. You’ll have a much better chance of success.

Invariably what prevents many from achieving higher levels of maturity is data. Missing, inconsistent and outright bad data will prevent most efforts to mature and certainly any effort to improve CX. So, when I have conducted maturity workshops I also invite data, CRM and IT stakeholders to the party, so they can collectively identify and discuss potential blockers and solutions on the fly. Another huge benefit is it also aligns support in understanding the impact of improving cross divisional challenges, from a maturity POV.

Action Plan:

Here’s are the recommended steps to pull this off:
1.     Schedule a Marketing Maturity Workshop (invite marketing, sales, CRM, data and IT)
2.     Agenda:
  • Introductions
  • Goal of Workshop (identify and improve marketing maturity across 9 key themes)
  • Review Maturity Model and get consensus on what level the marketing team is currently at across each of the 9 themes
  • Review the next rung up for each theme and begin to identify solutions to get you there
  • Create Project Plan and list of action items
  • Execute
  • Rinse and repeat
So how long does it take to go from zero to hero? Well, almost no one has the luxury of starting from scratch (bummer eh?). There are always legacy platforms, data silos and other integrations that slow the progress, so it really depends. A good general rule of thumb is one rung per year for enterprise and 2 rungs per year for SMBs. I’ve seen some companies go from crawl to BIC in less time, but the entire organization was fully committed and supported at the executive level.

Use this as a high-level roadmap in starting digital marketing maturity discussions. It should help keep the guard rails in place, funnel the collective focus, all while generating alignment and momentum.

Steven Kellogg

Monday, November 4, 2019

DMP, CDP, Data Lakes, Oh My...
A Data Primer for Marketers

As someone who started my professional career in Marketing, I along with many of you have a love/hate relationship with data. Love in the sense that having the right data is all-knowing and can bring you wealth, power and fame. Hate in the sense that not having all of it, or having it and it’s not complete, not accurate and/or not relevant. 

We all know customers fully expect a consistent, cohesive conversation, from the moment they first meet a brand to their last interaction, regardless of channel or device. To pull this off, marketers require…well, you know, data.

The lines between marketing expertise and data expertise continue to blur and may in fact already be almost indistinguishable. Marketers are now expected to be data scientists, or at least be able to have intelligent conversations with those who live and breathe data every day. (BTW that's marketers).

If you find yourself in this position, (and want to impress your colleagues with your data chops) below are definitions and use cases for common data platforms designed to get us marketers closer to customer experience expectations.

CDP (Customer Data Platform)

The biggest difference between a CDP and other types of data platforms is that a CDP is used to manage customer data. It is a data resource used by and typically controlled by marketers. While DMPs tend to focus on top-of-funnel initiatives, CDPs focus on mid to lower-funnel activities.

Think of a CDP as a central repository of siloed pockets of customer data; things like personal identifiable information (PII), transactional data, behavioral data, explicit data, offline data, call center data, etc. that marketers need in order to create specific customer segments or to drive 1:1 conversations. Additionally CDPs can also clean and dedupe this information. The real magic is that it matches all these touchpoints into a single customer record, holding and consolidating a customer’s interactions across channels/devices. Lastly it can feed this information to other platforms, like BI tools, DMPs and marketing automation platforms. It can be a dream come true for personalization, as well as customer insights, especially for those marketers currently frustrated by data silos.

If you are shopping for a CDP, one important point of comparison is the breadth of off-the-shelf integrations each solution has. Make sure the solution can easily integrate to your other data systems. Another point of comparison is the extent with which these customer profiles are updated in real time. These single customer records are useless if they are even a few hours old.

There are a host of CDP point solutions on the market as well as CDP functionality built into some existing enterprise marketing automation platforms. If you are interested in learning more, below is a list of CDP vendors to get you started. It is not an exhaustive list nor a recommendation, but a good place to start additional research:

DMP (Data Management Platform)

First of all, who came up with all these names? Data Management Platform, Customer Data Platform - good grief. I suggest a new acronym: CONFUSED (Customer Or Non-customer Frameworks for Unstructured or Structured Enterprise Data). Not bad eh? It only took me 5 days to come up with that 😊.

Anyway, a DMP is typically used for top of funnel initiatives as mentioned above. While it can ingest 1st party data, it focuses primarily on 2nd and 3rd party anonymous data. It’s great for web display ads, retargeting, look-alike modeling, and other lead gen efforts at scale. 

Publishers also use DMPs to monetize their data. Unlike CDPs that keep an ongoing historical record of activities, DMP data is often kept for shorter periods of time. Basically you can model the attributes of your best customers and have a DMP go out and find more just like them. One important point of comparison is match rate. How effective are they at matching these attributes and stitching together the identity dots across cookies, device IDs and IP addresses? 

If you’d like a more in-depth DMP primer, check out my DMP Primer video I recorded back in 2016. It’s still relevant today.

Below is a list of DMP vendors to get you started. It is not an exhaustive list nor a recommendation, but a good place to start additional research:

Data Lake vs. Data Warehouse

Data Lakes (as well as Data Warehouses) are both used to store big data. However a Data Lake holds raw unstructured data, the purpose for which is as yet undefined. Consider it a dumping ground for any data you think you might want to use sometime in the future. A Data Warehouse typically holds structured data that has already been filtered or processed for more specific purposes. A Data Lake is used by Data Scientists, while Data Warehouses are often used by the broader business. Companies often need both, as each requires different amounts of storage capacity and specialized tools to manage.

 BONUS: AI vs Machine Learning 

These two buzz words are thrown around everywhere, even in real estate broker ads. So what’s the difference?

According to the Artificial Intelligence Marketing Association, “Artificial Intelligence (AI) is the emulation of human intelligence process by machines be it a computer or an IOT device. The process involves learning (extracting meaningful insights and patterns), predicting (use the gathered information to help devices make plausible future decisions) and self-correcting (the art of getting more efficient every day). This is made possible by the three major wings of Artificial Intelligence — Machine Learning (ML), Natural Language Processing (NLP) and Deep Learning (Neural Networks). AI has established itself in every business sphere around the world -encompassing everything from Rule-based machine learning to visual classification. Its applications range from object recognition to preventing high-end cybersecurity threats.”

Artificial Intelligence is what Tesla uses to drive cars autonomously. It’s what manages intelligent stock trading systems. Here are some very interesting stats about AI, published by

Machine Learning is what the iPhone uses to blur backgrounds in Portrait mode. It’s what virtual assistants use in their speech algorithms, (using NLP Natural Language Processing). Waze, Google Maps, any of the driving direction apps use lots of machine learning to find you the quickest way there. 

All in all, it’s a great time to be alive and enjoy all this cool technology! Hopefully you now have a better understanding of these terms. Now go impress your favorite data architect, or better yet, your boss.

Steve Kellogg

Monday, September 2, 2019

The Customer Circle of 5ths

We all know CX will likely become the main key competitive differentiator at some point. It already has in some sectors. To help drive this home, I recently created what I am calling the 'Customer Circle of 5ths', to help Marketing, Sales, Service and PR/Brand Departments visualize how each contributes to this, and what the cause/effect relationships between them are, from the customer's POV. 

This also turned out to be a simple visual that identifies and delivers the core criteria almost every customer needs in order to say 'yes'.

In music theory, the circle of fifths is the relationship among the 12 tones of the chromatic scale. In this article we'll explore the choreographed relationships between marketing, customer experience and branding, using my own version of the Circle of 5ths.

The goal of the Circle of 5ths is to quickly understand how CX, Marketing and Branding each contribute to delivering the most important criteria customers need in order to say 'yes'. So what are the most important criteria?
Think about any purchase decision you've ever made. There were 3 things that likely had to be in place before you said 'yes':
  1. Relevance
  2. Trust
  3. An Emotional Connection
Lets take the example of booking a flight. You had to first find an airline that went to your destination (relevance). Then you had to have confidence that their planes were safe (trust). But those two things alone usually aren't enough to say yes, all other things being equal. There had to be an emotional connection. So, in our example if you had established relevance and trust with 2 airlines, but you only had a positive emotional connection with one of them, that's who you'd very likely have chosen.

So how does marketing, CX and branding all contribute to providing relevance and trust, while fostering a positive emotional connection? In short, CX drives an emotional connection to brand, which drives acceptance/engagement in further marketing, fueled by a CTA that contributes to a positive interaction, which starts the cycle all over again.

Let's look at a B2B example:

A lead might enter the Circle of 5ths at any part of the cycle, but the flow is always the same. Each time they complete the circle, ever increasing levels of relevance, trust and emotional connections are (hopefully) established.

So what actions can you take from this? You see the dependencies these have on each other. If one falls short, the entire circle suffers.

Stating the obvious - whether you are in marketing, sales or customer service, you have to be ruthless about creating a positive interaction. Every activity you are involved in that the customer either sees, reads or hears will impact the whole circle.
  • For marketers that means having a full view of all interactions (both positive and negative) and adjusting messaging accordingly. Insist that CTAs are relevant and easy to act on. The adage, help, not hype fully applies here.
  • For marketing automation, that means enabling technology that delivers a different message to everyone, based on certain rules related to the latest achieved levels within the circle of 5ths.
  • For sales and service that means having a full view of all interactions (both positive and negative) throughout the customer journey and adjusting responses accordingly.
So if you're looking for a simple way of explaining how marketing, branding and CX all support each other and/or visualizing the impact of a single positive interaction, see if this helps.

Steve Kellogg