For small companies, Marketing Mix Modeling (MMM) is critical since it offers priceless insights into the road for success of their marketing initiatives and facilitates more effective use of their limited resources. Small businesses can use MMM to make data-driven decisions to maximize their marketing strategies by analyzing the effects of different marketing channels and methods on their overall performance. (more…)
Marketing Mix Modeling (MMM) is a statistical analysis technique used to measure the effectiveness of various marketing tactics and their impact on sales and other key performance indicators. However, traditional MMM vendors and advertising agencies often struggle to meet the evolving needs of brands in today’s fast-paced digital landscape. (more…)
Implementing Marketing Mix Models (MMMs) requires a cohesive effort from various key stakeholders: the client, agency/agencies, and the MMM vendor. A structured approach is essential to navigate the complexities of media and budget planning. (more…)
In the intricate landscape of Marketing Mix Modeling (MMM), success is intricately tied to its harmonization with client requirements, particularly in the realms of media and budget planning. A well-structured MMM framework becomes pivotal, offering timely insights that empower marketing and media teams in their decision-making processes. Notably, addressing the misalignment in cycle timing between MMM outputs and client needs emerges as a critical focal point.
In the dynamic consumer goods landscape, CPG retail analytics plays a pivotal role in deciphering market trends and consumer behavior. By leveraging advanced data analytics tools, CPG companies gain invaluable insights into product performance, inventory management, and customer preferences. (more…)
In digital marketing, marketing mix modeling is becoming more and more significant. Marketers are finding it harder to gauge their initiatives’ success as data-walled gardens and cookie-killing tactics proliferate. (more…)
3 top ways companies are losing hiring great Data Science talent:1. Archaic rules around FT hiresWe all know of so many talented folks with over a decade of specialized DS experience who most companies can’t afford full time, but they are available part time, or as a consultant.They are not interested in 10 interviews over 2 months, for a job guarantee, that doesn’t really exist in this market.They are done looking for them.If you want great talent with experience, companies have to learn how to mend their policies to use them.
I’ve met a lot of talented candidates lately who are eager to learn and excited to get a new job. My advice to them and anyone looking is this:1. Take Networking seriouslyHaving a strong network is important in helping, and being helped. This is a 2 way street.It may or may not lead to a job, but there are good people who may not mind sharing the name of hiring manager.But please don’t ask them to refer you if you don’t know them.It’s okay to reach out to HR of that role and send a PM.Also, engage with other people’s posts and comment.
I’ve met a lot of talented candidates lately who are eager to learn and excited to get a new job. My advice to them and anyone looking is this:1. Take Networking seriouslyHaving a strong network is important in helping, and being helped. This is a 2 way street.It may or may not lead to a job, but there are good people who may not mind sharing the name of hiring manager.But please don’t ask them to refer you if you don’t know them.It’s okay to reach out to HR of that role and send a PM.Also, engage with other people’s posts and comment.
Should you invest in a new MMM partnership?Or an Attribution vendor?Maybe, maybe not.Because at the end of the day, the ROIs and contributions, are rather, sticky regardless of which vendor you pick.The key differentiator in my opinion, is SPEED.Second, tool usage.I think a lot of #marketing folks ND #brands run after the best performing models, vs the fastest one.Because the delta between those 2 vendors is this.- One vendor gives your results when you need- The other vendors gives you results half a year later.Stop investing in those vendors. The methodology never makes up for delayed decisions.
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