5 Models for Engaging Top Marketing Analytics Talent

You probably know that artificial intelligence and machine learning are the latest hot concepts in modern marketing, and are being successfully applied to prospect segmentation and targeting, customer attribution, and many other vital marketing activities.

So, you’ve decided your marketing organization should explore the potential benefits of applying advanced analytical methods to your marketing data. How do you take the first step?

For many companies, the lowest risk approach is to use outside help. If your marketing organization has little prior experience in data science, creating an in-house program almost guarantees that you’ll make a large investment before you see a penny in return.

If you want to know some of the other reasons for engaging with consultants or contractors rather than direct hires, here are some good business reasons for hiring external help.

There are a number of models for engaging with an outside firm or individual, each with its own pros and cons. I’ll describe the five most common and you can decide what’s best for your business.

You can hire a team or individual on a contract where you only pay for the work done on your project. This is similar to hiring a lawyer or a law firm to assist your company with a legal issue.

Pros

You can control the cost of this type of arrangement, by putting a limit on hours or capping the overall budget. If you feel the project is not going well, you can usually cut your losses with minimal repercussions, as you’re not bound by a long-term contract.

Cons

You generally pay more than you would pay a direct hire employee to do the same work, because the company or individual you are contracting with must build overhead into their hourly rates. This can be offset by leveraging talent from lower cost

In this case you negotiate a flat monthly fee for a team that works full-time to complete your projects. The team works as a unit of your company until the agreed upon projects are finished.

Pros

Because the team is focusing exclusively on your projects full-time, they don’t suffer from the inefficiencies of workers who are constantly switching between clients and projects. They will learn the intricacies and nuances of your business. The team will develop stronger relationships with in-house employees because communication is more consistent. The labor cost of a full-time team is significantly lower than paying hourly contractors.

Cons

You will need to maintain a steady flow of work.

In this scenario you work with an outside firm or individual to build a scope of work, then agree on a single flat fee that covers the entire job.

Pros

You’re paying for the completion of a well-defined set of deliverables, no matter what it costs the contractor company or how long it takes. Your cost is completely predictable.

Cons

Similar to hiring a dedicated team, if you later decide your relationship isn’t working, or the quality of work isn’t stellar, you are essentially stuck paying the full amount of the contract. You also generally pay more for this type of agreement, because the contractor must build into their costs the risk of scope gaps. They still have to pay their employees, no matter how long it takes to complete the work. Also, in most cases, the work effort to scope the project needs to be completed first and since the requirements process is unpredictable, there will usually be an initial phase that is completed at hourly billing rates. After the scope of work is defined and agreed to a fixed fee can be calculated.

This is the same as paying a single fee like #3, but in this case the contractor only gets paid if their work achieves an agreed upon result. For example, if a consulting firm guarantees that they can improve your direct mail response rate from 1% to 2.5% or better for your annual mailing campaign, they only get paid if they execute on that promise.

Pros

You only pay if your project succeeds. Great, right?

Cons

Because the contractor is taking all the risk, this tends to be the most expensive option. Even if you’re successful, your ROI will be lower.

Hire an expert vendor to build a dedicated team that converts to in-house employees. Exactly like a dedicated team, but at some point in time the hiring company takes over management of the team and brings them on as regular employees. This transfer can also be optional, in which case the company can choose to transfer the team by paying a buy-out fee, or end the relationship. Selecting a vendor with expertise in low cost locales can result in significant cost savings.

Pros

For companies that are committed to advanced analytics in their marketing team, this offers the benefits of a dedicated team with a contractual guarantee that they can onboard that particular set of talent. The contract firm has a high level of domain expertise in hiring data scientists and related roles. You have a chance to try out a team and evaluate results before making the decision whether to continue the relationship or not, if you use a buy-out option.

Cons

If you have an upfront agreement to take on the team after a certain period, you’re making a relatively large commitment. If you choose to make the team transfer optional, the overall cost will be higher because the contracting firm assumes the risk that you will decline the transfer option.

When your marketing organization is just beginning to explore the business uses for big data and advanced marketing analytics, the best advice is to start slow and learn before committing to a complete transformation of your marketing practices.

There’s a common misperception that engaging top-level talent is too expensive. But you should be able to use one or more of the models above to reduce risk and improve your long-term success, no matter what your budget. You could hire a highly experienced data scientist for a few hours a week to help you define the goals of a bigger project, for example. Once you understand what you want, then you can move on to hiring an individual or team to execute that project.

And if you’re in the US, don’t overlook the potential cost savings of hiring overseas talent. My company has employed extremely talented engineers, data scientists and analysts from Eastern Europe at a fraction of the cost of North American employees with similar experience and skill sets. This report from HackerRank backs that up: 7 of the top 20 countries for programmer talent are in Eastern Europe.

Whichever way you decide to go in your marketing analytics journey, please feel free to contact me if you’re searching for talent or have questions about data science hiring trends and best practices.