How do agencies distinguish themselves from the competition?

For marketing, advertising and media agencies, an emerging trend involves the creation of custom analytics solutions that leverage data science technologies, particularly AI and Machine Learning. Understanding that clients want to know that you’ve “solved this problem before,” offering a suite of analytics products focused on key client needs can be a difference maker when it comes to winning, retaining, and expanding client relationships.

Automated data science tools are not only powerful but are becoming easier to use for team members of all skill levels. In parallel, marketing departments and agencies are embracing AI and Machine learning at a growing rate and with increasing success. From media mix, churn and attribution modeling to media spend, content delivery and journey optimization, AI is positively impacting results.

At Lityx, we have been leveraging AI and Automated Machine Learning (AutoML) for more than a decade to help marketing teams understand what is working, what needs help and how to automate solutions for repeat use. For more than a decade, our team of Data Scientists have leveraged the LityxIQ AutoML platform to build and automate solutions that are repeatable, scalable, and easily customized to a particular client situation.

Here are three key steps to successfully developing ownable analytics products:

• Focus on Key Needs
• Establish Solution Models that address these needs
• Leverage an AutoML platform that your entire team can use

Focus on Key Needs
Ask your account teams which analytics needs are most prevalent among your clients and chances are that 3-4 will quicky rise to the top. Often, it will be something that has long frustrated the client, such as optimizing the media mix, streamlining the customer online purchase journey or reducing churn.

Align this learning with those tasks that seem to absorb much of your analytics team’s time, and you will have narrowed your needs list further. Prioritize this list based on timing, budget and team availability.

Establish Solution Models that address these needs
Understand how your analytics team has solved these concerns in the past. Which approach worked the best? What is needed to make it work better or faster? Often, consulting with an outside resource with deep experience solving the same problems for a range of organizations, can add additional perspective and accelerate the problem.

The Lityx analytics team consults regularly with clients via a Proof of Concept (POC) test to help with creating smart, repeatable processes for solving core client needs. This additional horsepower shortens timelines, while creating additional value for the solution and end clients.

Leverage an AutoML platform that your entire team can use
Machine Learning technology enables analytics teams to quickly analyze large volumes of data and create models and larger solutions that get smarter over time. A key is finding a platform that is robust, yet easy-to-use.

To maximize the production of your analytics team, choose an AutoML platform that is designed for a full range of experience levels. This added efficiency will come in handy as more clients tap into your new analytics products. Check out this article on Three Keys to Choosing an AutoML platform for a deeper dive.

Marketing firms constantly struggle with remaining relevant and differentiated in an ever-changing business environment. The shortest pathway to long-term success involves leveraging internal and external resources that help create a set of tools and techniques to solve a common client challenge and then bundling those into an agency-branded product. And perhaps best of all, these new, repeatable AI analytics solutions create new revenue streams with stronger margins.