Turn your data geeks into customer geeks

an image that says 'I love data"

an image that says 'I love data"What would you do if you had so much data about your customers that you know could know (almost) everything about your customer when they contacted you? Better yet, what if you had the ability to instantly know the exact offer for service or product that would pitch the right ‘sales’ approach that your customer would immediately sit up, take notice and spend money?

Most of you would jump at the chance to have this information about your clients.  You may be willing to open up the checkbook for a huge amount of money to make this happen.  What if I told you that you don’t need to do much more than get a better grasp on your data and understand how to use that data to build a 360 degree view of your customer?

Granted, you may need to collect a bit more data (and perhaps find new types of data) and you may need to implement some new data management processes and/or systems, but you shouldn’t have to start from scratch  – unless you have no data skills, people or processes. For those companies that already have a data strategy and a team of data geeks, building a customer-centric view with data can be extremely rewarding.

Many companies consider themselves ‘customer-centric’ and have built programs and processes in order to ‘focus on the customer.  They may have done a very good job in this regard but there’s more than can be done. Most organizations have focused on Customer Relationship Management (CRM) as a way to help drive interactions with clients.  While a CRM platform is important and necessary, most of these platforms are nothing more than data repositories that provide very little value to an organization beyond the basics of ‘we talked to this person’ or ‘we sold widget X to that customer.’

Utilizing proper data management and the data lake concept, companies can begin to build much broader viewpoints into their customer base. Using data lakes filled with CRM data along with customer information, social media data, demographics, web activity, wearable data and any other data you can gather about your customers you (with the help of your data science team) can begin to build long-term relationships built on more than just some basic data.

In addition to better relationships with your customers, a data-centric approach can help you better predict the activities of your customers, thereby helping you better position your marketing and messaging. Rather than hope your messaging is good enough to reach a small percentage of your customer base, the data-centric approach can allow you to take advantage of the knowledge, skills and systems available to you. Additionally, this approach will allow your data team to create personal and individual programs and messaging to help drive marketing and customer service.

Originally published on CIO.com

Opportunity Lost: Data Silos Continue to inhibit your Business

An image of data silos

An image of data silosAccording to some estimates, data scientists spend as much as 80% of their time getting data in a format that can be used. As a practicing data scientist, I’d say that is a fairly accurate estimate in many organizations.

In the more sophisticated organizations that have implemented proper data integration and management systems, the amount of time spent sifting through and cleaning data is much lower and, in my experience, more in line with the numbers reported in the 2017 Data Scientist Report by Crowdflower.

That report indicates a better balance between basic data-wrangling activities and more advanced analysis:

  • 51% of time spent on collecting, labeling, cleaning and organizing data
  • 19% of time spent building and modeling data
  • 10% of time spent mining data for patterns
  • 9% of time spent refining algorithms

Closing the Gaps

If we think about this data transformation in terms of person-hours, there’s a big difference between a data scientist spending 80% of their time finding and cleaning their data and a data scientist spending 51% of their time on that same tasks. Closing the gap begins with demolishing the data silos that impede organization’s’ ability to extract actionable insights from the data they’re collecting.

Digital transformation projects have become a focus of many CIOs, with the share of IT budgets devoted to these projects expected to grow from 18% to 28% in 2018. Top-performing businesses are allocating nearly twice as much budget to digital transformation projects – 34% currently, with plans to increase the share even further to 44% by 2018.

CIOs in these more sophisticated organizations – let’s call them data-driven disruptors – have likely had far more success finding ways to manage the exponential growth and pace of data. These CIOs realize the importance of combating SaaS sprawl, among other data management challenges, and have found better ways to connect the many different systems and data stores throughout their organization.

As a CIO, if you can free up your data team(s) from dealing with the basics of data management and let them focus their efforts on the “good stuff” of data analytics (e.g., data modeling, mining, etc.), you’ll begin to see your investments in big data initiatives deliver real, meaningful results.

Originally published on CIO.com

Foto Friday – Shades of Gray

Image - Shades of Gray

This is a black and white of a sunrise over Sprague Lake in Rocky Mountain National Park, Estes Park Colorado. Made with Sony A7rIII and Sony 16-35 2.8 GM Lens. Click the photo to be taken to a larger version on 500px.

See more photos at my dedicated Photography website. If you like my photography, feel free to support my addiction habit by purchasing a copy for your wall and/or visiting Amazon (affiliate link) to purchase new or used photographic gear.

Image - Shades of Gray

You Need a Chief Data Officer. Here’s Why.

Image of the word "why"

Image of the word "why"Big data has moved from buzzword to being a part of everyday life within enterprise organizations. An IDG survey reports that 75% of enterprise organizations have deployed or plan to deploy big data projects. The challenge now is capturing strategic value from that data and delivering high-impact business outcomes. That’s where a Chief Data Officer (CDO) enters the picture. While CDO’s have been hired in the past to manage data governance and data management, their role is transitioning into one focused on how to best organize and use data as a strategic asset within organizations.

Gartner estimates that 90% of large global organizations will have a CDO by 2019. Given that estimate, it’s important for CIOs and the rest of the C-suite to understand how a CDO can deliver maximum impact for data-driven transformation. CDOs often don’t have the resources, budget, or authority to drive digital transformation on their own, so the CDO needs to help the CIO drive transformation via collaboration and evangelism.

“The CDO should not just be part of the org chart, but also have an active hand in launching new data initiatives,” Patricia Skarulis, SVP & CIO of Memorial Sloan Kettering Cancer Center, said at the recent CIO Perspectives conference in New York.

Chief Data Officer – What, when, how

A few months ago, I was involved in a conversation with the leadership team of a large organization. This conversation revolved around whether they needed to hire a Chief Data Officer and, if they did, what that individual’s role should be. It’s always difficult creating a new role, especially one like the CDO whose oversight spans multiple departments. In order to create this role (and have the person succeed), the leadership team felt they needed to clearly articulate the specific responsibilities and understand the “what, when, and how” aspects of the position.

The “when” was an easy answer: Now.

The “what” and the “how” are a bit more complex, but we can provide some generalizations of what the CDO should be focused on and how they should go about their role.

First, as I’ve said, the CDO needs to be a collaborator and communicator to help align the business and technology teams in a common vision for their data strategies and platforms, to drive digital transformation and meet business objectives.

In addition to the strategic vision, the CDO needs to work closely with the CIO to create and maintain a data-driven culture throughout the organization. This data-driven culture is an absolute requirement in order to support the changes brought on by digital transformation today and into the future.

“My role as Chief Data Officer has evolved to govern data, curate data, and convince subject matter experts that the data belongs to the business and not [individual] departments,” Stu Gardos, CDO at Memorial Sloan Kettering Cancer Center, said at the CIO Perspectives conference.

Lastly, the CDO needs to work with the CIO and the IT team to implement proper data management and data governance systems and processes to ensure data is trustworthy, reliable, and available for analysis across the organization. That said, the CDO can’t get bogged down in technology and systems but should keep their focus on the people and processes as it is their role to understand and drive the business value with the use of data.

In the meeting I mentioned earlier, I was asked what a successful Chief Data Officer looks like. It’s clear that a successful CDO crosses the divide between business and technology and institutes data as trusted currency that is used to drive revenue and transform the business.

Originally published on CIO.com.

Customer Engagement: A Data-Driven Team Sport

Customer Engagement: A Data-Driven Team Sport

Customer Engagement: A Data-Driven Team SportWhat would you do if you had so much data about your customers that you know could know (almost) everything about your customer when they contacted you? Better yet, what if you had the ability to instantly know the exact offer for service or product that would pitch the right ‘sales’ approach that your customer would immediately sit up, take notice and spend money?

Most of you would jump at the chance to have this information about your clients.  You may be willing to open up the checkbook for a huge amount of money to make this happen.  What if I told you that you don’t need to do much more than get a better grasp on your data and understand how to use that data to build a better overall view of your customer?

Granted, you may need to collect a bit more data (and perhaps find new types of data) and you may need to implement some new data management processes and/or systems, but you shouldn’t have to start from scratch unless you have no data skills, people or processes. For those companies that already have a data strategy and a team of data geeks, building a customer-centric view with data can be extremely rewarding.

This customer-centric, data-driven approach is what most organizations are driving toward with their digital transformation initiatives.  Graeme Thompson, Informatica CIO, has argued for the importance of a customer-centric approach for some time. According to Graeme:

“You have to think about [digital transformation] in a connected way across the entire company.  It’s no longer about executing brilliantly within one functional silo. CIOs see the end-to-end connection [of different functions] across the entire company – how all these different processes need to work together to optimize the outcome for the enterprise, and, most importantly, for customers.”

Many companies consider themselves ‘customer-centric’ and have built programs and processes in order to ‘focus on the customer.  They may have done a very good job in this regard but there’s more than can be done. Most organizations have focused on Customer Relationship Management (CRM) as a way to help drive interactions with clients.  While a CRM platform is important and necessary, most of these platforms are nothing more than data repositories that provide very little value to an organization beyond the basics of ‘we talked to this person’ or ‘we sold widget X to that customer.’

These ‘customer-centric’ companies can be even more custome​_r-centric by becoming a data-driven organization. They have taken a small subset of customer data and built their entire customer engagement process around that data set.  That approach has worked OK for years, but with the data available to companies today, there’s no need to rely solely on that small data set.

Utilizing proper data management and the data lake concept, companies can begin to build much broader viewpoints into their customer base. Using data lakes filled with CRM data along with customer information, social media data, demographics, web activity, wearable data and any other data you can gather about your customers you (with the help of your data science team) can begin to build long-term relationships built on more than just some basic data.

In the white paper titled ‘Game Changers: Meet the Experts Behind Customer 360 Initiatives,’ there are some very good examples of how companies have become much more customer-centric and data-driven.  A few examples from the paper are:

  • FASTWEB uses Salesforce as much more than just a CRM. Their Salesforce instance includes a view into the customer by providing lists of latest invoices, the status of those invoices, payments and other key customer relationship data.
  • PostNL, a mail, parcel and e-commerce company, has changed their focus from simple ‘addresses’ to one that is focused on the customer by focusing first on data, then on the customer. No longer is their focus on getting a package from point-A to point-B, it is on using data to ensure the customer’s needs are met.
  • Bradley Corporation, a 95-year old manufacturer of plumbing fixtures implemented a Product Information Management system to ensure that data is up-to-date and accessible for their more than 200,000 products. This system simplifies the ability for their customers to find the right parts quickly and easily.

In addition to better relationships with your customers, a data-centric approach can help you better predict the activities of your customers, thereby helping you better position your marketing and messaging. Rather than hope your messaging is good enough to reach a small percentage of your customer base, the data-centric approach can allow you to take advantage of the knowledge, skills and systems available to you and your data team to create personal and individual programs and messaging to help drive marketing and customer service.

Originally published on CIO.com

Marketers – You have too many choices

Marketing Technology Landscape Supergraphic (2018)

I have a little secret for everyone in the world of marketing: You have too many choices.

There are way too many technology platforms in existence today. Too many ‘tools’ and too many products.  You have too many choices when it comes to getting your work done. Let’s take a quick second to glance at Scott Brinker’s MarTech 5000 landscape:

Marketing Technology Landscape Supergraphic (2018)

I’m sorry, but that’s just too many choices; especially when put in the hands of people that don’t really understand the long-term implications of multiple technology platforms.

Sure, there may be a formal selection process (in my experience, there’s not…or at least it isn’t followed) and  rarely is there a strategic vision when it comes to MarTech. There’s a bunch of tactical ‘needs’ for why a particular type of platform is needed/wanted and even a hand-wave toward ‘strategy’ but rarely is there an in-depth review of how a new platform will make things better for the marketing team and the organization as a whole and (ahem…most importantly) help reach the strategic objective of the organization.

Too many choices can be a real problem.  Need an ‘optimization’ platform for A/B testing (or other optimization issues)?  I’m sure you can find 30 or 40 vendors out there selling some version of a platform that will do what you need it to do.  Do you take the time to run a thorough selection process or do you find the first one that fits your ‘right now’ need and your budget and push ‘buy’?  Based on my experience, people do the latter and pick the first one they find that does what they need to do.  They find a solution to the problem they have today with very little to no thought put into how that platform will integrate into their broader organization’s ecosystem and/or whether the solution will solve their problem tomorrow.

Don’t get me wrong. Personally, I love the possibilities that these choices offer an organization, but only if proper governance is used when selecting and implementing these choices.  Based on my conversations with clients and marketing /  IT professionals over the last few years, there’s very little of this happening.

Over the last 3 years about half the projects I been asked to be a part of are projects to help simplify the  ecosystem within an organization.  I’ve seen companies with over 100 platforms being used within the marketing team with very few of those systems able to talk to each other — and the lives of the marketing team had become a living hell because they had too many systems, too little control of their data and too little insight into what they are able to do, how to do things and who to go to for help.

What’s the solution?

There’s not an ‘easy’ answer.

It will take hard work, focus and a real drive toward reducing the complexity within your marketing organization.  Think of it as putting your team on a diet – a MarTech diet.  When you ‘need’ (by the way – its rarely a ‘need’ and usually a ‘want’ in these cases) some new function that you just can’t live without – check your existing platforms before going out to buy some new tool. If you are absolutely sure you don’t have the functionality in your existing platforms, take a look at what you’re trying to do and think about if its an absolute need and not just a ‘want’.  More importantly, think about the long term vision / strategy of the organization – how does ‘MarTech Platform X’ get you there?  If you can’t easily answer the question, it might be best to try to find a way to do what you need to do with your existing ecosystem.