Econometrics (or MMM) has been well established in marketing for a number of years. Central to it’s ethos is the use of advanced statistics in financial markets and economics to build predictive models. These models can then be ‘decomposed’ to isolate the impact of individual media on company sales. This in turn gives a return on investment of each of the tactics employed, which together with response curves and diminishing returns enables a company to make informed investment decisions on their optimal media mix and laydown. For more about our econometrics and ROI offering visit our page on it here.
More recently the proliferation of data has led to an explosion in data science. This is incredibly useful when you have large complicated data sets and you are trying to interpret them and discover relationships. Often though, the data dominates the science. Companies (and agencies in particular) recently have had something of an arms race in this area, but it is almost always a case of style over substance – they create great stories, branding, logo’s and names to show off their analytics offering – but as a rule of thumb if they can’t explain it in a simple way then it is at best generic, and at worst simply isn’t real.
We do use data science, but we keep a keen focus on the science. We ask hypotheses, and we test those hypotheses by sourcing the right data, and using tests, statistics and applying rigour. All data science is presented in an open and honest way.
The primary area we use data science is in understanding language. Specifically, in using AI to understand the emotions and psychologies behind what is being said in the media about a brand or about topics. For more on this visit our page on media analysis here.
On the left are the four key tenets to which we work when it comes to analytics and data. We offer a fully open approach, discussing the approaches and methodology in as much detail as required.
As a part of all our offerings there is a low cost opening analyses. In econometrics projects we offer a feasibility study, allowing a client to break the project early if the data is unsatisfactory. In media analysis we always recommend a fast dip as a first port of call – often this turns out to be all a client needs, but if they want more it allows questions to be informed, hypotheses to be generated and the project to be much more targeted and effective.
Alex is the founder of Independent Marketing Science, Ballpark Crisis Ltd.
I have experience in multiple agency disciplines, having worked in creative, media and communications agencies as well as in local, regional, and global roles. I have proven capabilities in building teams, products, solutions and developing analytically based business, both independently as a P&L and as part of integration into the wider agency business.
I have built products using econometrics, AI and machine learning focussed around paid, earned and social media. Integrating multi-disciplinary techniques to build advanced, effective and critically understandable and useable solutions for clients worldwide.
I have worked with clients that range from small, niche and start-ups, to global blue-chip enterprises. From FMCG/CPG, Services, Automotive, Financial, Travel, Health, and government initiatives. Below is a small selection of some of these clients…..
David is the Chief Technical Officer of Independent Marketing Science, Ballpark Crisis Ltd.
My background is across both media agencies and independent consultancies, working for clients based in the UK and globally. I have experience across Market Mix Modelling (Panel, Multiplicative, Nested), Pricing and Promotional analysis, Match Market Testing, Attribution Modelling, Consumer Segmentation, Purchase Funnel Analysis and Brand Attribute studies. While managing teams, I have worked closely with clients to ensure the right analytical techniques are used to answer bespoke questions.
Through my career I have built bespoke analytical products for client use, and have driven the development of in-house analytical software. These tools encompass regression, simulation & optimisation, dashboarding and automated reports.
I have experience across a wide array of clients – including Retail, FMCG, Automobile, Luxury, Beverages, Entertainment, Charity, Oil & Gas, Clothing, Pharmaceutical and Finance. A selection of these are shown below….
Tori is the Head of Comms Analytics at Independent Marketing Science, Ballpark Crisis Ltd.
My skillset in analytics helps guide business communications by understanding who to communicate with, how to communicate, and ultimately – how to influence behaviour change. The analytics skills I bring to the fore vary from advanced social listening, web-based analytics and search behaviour, media monitoring, and audience profiling.
In my career I’ve designed custom digital analysis mapping patient mindset through the disease journey for companies like Novartis & Roche, helping companies relate to what patients actually feel, rather than just the diseases they manage. I have created CEO benchmark ranking LinkedIn performance for tech giants Microsoft & Capgemini. And restructured Benin’s national approach to malaria prevention.
Throughout my career I have produced business changing insights & reports from healthcare, to social impact work, to big tech to B2B & corporate affairs. I was a 30 under 30, until I turned 30 and then decided to leave the agency life to focus purely on the good I can do through data analytics and consultancy.
Andy is the Client Advisor and Consultant at Independent Marketing Science, Ballpark Crisis Ltd.
My background is in sales and marketing, having worked for marketing, data and communications agencies in the UK and in the US and Asia. Proving the effectiveness of marketing activity has been at the core of my work and now I help brands navigate the effectiveness journey.
My focus is on ensuring that clients’ business needs, questions and challenges are at the heart of the work we do. To use data and analytics to make a tangible impact on a client’s business, its growth strategy, specific KPIs, or other key objectives. Use data for commercial purposes and outcomes.