NUMERATI empowers marketeers make sound, fact-based decisions using bespoke marketing research and analytics particularly in these challenging, continuously-changing times.
NUMERATI does this through
1. The use of advanced statistics (attitudinal-behavioral-demographic-based segmentation, econometrics-/regression-based modelling)
2. Providing advice in optimizing returns on existing marketing research and learning programs
3. Designing marketing learning and research programs which include bespoke metrics development, dashboard development, qualitative/quantitative research results "deep-dives" and integration, and what-if simulation
4. Providing strategic planning advice and consultancy
There are a lot of jokes about consultants, mostly identifying them (us?) as "people you pay to tell you what you already know".
But I think this is what - at its core - what consultants do: to empower and inspire you to do what to do.
In my job, I can only use numbers and gathered data, analyzed and scrutinized against a specific problem that both clients and I have uncovered as the "root problem". I use these numbers and data in order to create potential options for clients, identifying the opportunities and the risks associated with each option.
The decision remains with the client - in terms of which action to take and whether to implement the decision with the required rigor.
We can claim to be experts of your business - but at the end of the day, it is your business. You are the stakeholder. We can help you make decisions - and implement those decisions. But we can't make those decisions for you.
At the end of the day, you as the client will have to take the leap.
It is quite amazing how marketeers are now so enamored by "the social".
But as early as the 1990s, I have seen studies that showed that "recommendations from friends, family, and other people" are as effective or more effective than any form of advertising. A former colleague was not convinced by it - to the point that she junked the research and called it "irrelevant and potentially, not valid".
I guess the problem was, when you say "recommendations are far better than any form of bought advertising", you're essentially saying that "you don't have so much control over your brand messages as you have earlier thought". that "your brand is essentially at the mercy of consumers".
the truth is, "it" - The Social - has always existed.
we're the ones waking up to its power.
the conversations are louder, the demand to be heard is more pressing, and the clamor to "own" (or "disown") the brands that we thought we had control over is not about to end.
If business objectives are not quantified - it's nothing but a set of big, hairy audacious goals.
If RoI is not quantified - it's nothing but useless chest-thumping, "I-saved-the-company/world-all-by-myself" denial of what's real.
And oh - you can't set business objectives unless you know where you currently are - if your business sucks now, it doesn't help if you deny that it sucks or 'beautify' it with "yes, we suck but...". No "but's" about sucking, dude.
If you suck, you suck. Period. Admit it. Move on. Set new directions - real, realistic directions.
I picked this one up from Paul Isakson's entry on Dieter Rams, one of the great voices in the world of design and innovation. I reread the Ten Principles of Good Design (or Ten Commandments, I think they sometimes are called) and indeed, they are in my opinion relevant to the world of strategic communications planning.
| For what is strategic communications planning but the creation and design of an experience between a brand and its consumers - so the brand becomes a part of the life of the consumer and the consumer, a part of the brand? |
The world of media buying has shifted dramatically due to changes in the consumer landscape as digital media became a significant part of the lives of consumers.
Through a friend on Facebook, I saw this video from PSFK.Com on the 'Secrets of a Killer Media Buyer: Future Success'.
There are three things that I got from the video:
1. Media buying is still about value-creation. At the end of the day, it is about creating value for clients and generating the best deal.
2. However, the definition of value has changed: Value is no longer merely dollars-saved or the "best deal that you could negotiate and seal with all the bells and whistles for the clients for the lowest price possible". Value is now about
(a) utility to clients - what's in it for them, they who are investing the money (b) utility to consumers and audiences - what's in it for consumers
3. To achieve the best deal and realize the ultimate value for clients, you need data. Because technology has paved the way for consumers to be entertained in terms of quantity and quality, we need data.
(a) The usual lines between 'traditional media' and 'non-traditional media' have been blurred by technology. "Video" no longer is just about TV - it now encompasses online videos (and the ad platforms supported by it), mobile videos, game consoles, handhelds, and even outdoor/in-store. "Radio" is no longer just what one hears on a radio set or on the car - but also in-mobile, on-the-web, on-demand, on-the-palm... And press and magazines.
(b) To navigate through these choices, you will need data - how do consumers shift from one medium to another and why? [The "why" bit is almost-always missing - and is always a point of contention between me and most of the media planners-buyers that I work with. But that's another story.]
(c) The kind of data that we need no longer will center on "how many people are exposed" - the usual impression-based metrics and currencies. The kind of data that we need will need to encompass audience motivations, mindsets, and response.
In my experience of setting up and of being a part of internal and client-based analytics and knowledge-teams, I have learned that the structure of the team is critical not in defining the roles and responsibilities. It is also critical in the hiring process and in optimizing the search for insights.
There are three types of expertise that are needed to create a successful analytics team:
1. The Data Technicians, who gather, manage, and 'qualify'/'purify' the data one is getting - whether internally or externally
2. The Data Analysts, who take the information from the Data Technicians and analyze them using mathematics, statistics, econometrics and other techniques in response to questions and hypotheses
3. The Knowledge Integrators, who take the analyses, integrate them with other sources of information (such as consumer feedback, market evolution, business and brand lifecycle) and make them relevant to questions raised
All three are equally important and play a critical set of interrelated roles and responsibilites in the search for evidence-based insights.
One could be tempted to hire people who can do all three - but in my experience, it is difficult.
1. Finding potential candidates who can do all three roles is one difficult affair even with the help of experienced headhunters. They are a rare breed.
2. If one did manage to hire one who could do all three, I believe that one or two of the responsibilities could be sacrificed. And that is a great risk.
Setting up an effective analytics team needs great thought and foresight.
In marketing, customer lifetime value (CLV), lifetime customer value (LCV), or lifetime value (LTV) is the net present value of the cash flows attributed to the relationship with a customer.
The use of customer lifetime value as a marketing metric tends to place greater emphasis on customer service and long-term customer satisfaction, rather than on maximizing short-term sales.
The formula for calculating CLV is:
... where GC is the yearly gross contribution per customer, M are the associated costs in retaining customers, n is the number of years, r is the yearly retention rate, and d is the yearly discount rate.
1. In this social age, where connections between customers are far stronger because of social-media enablers/technology, is this formula still valid?
Certainly, the "gross contribution" of a customer should take into account not just her own purchases - but also the impact that her purchases have on her experience and her propensity to recommend the same brand (or not) to others.
Additionally, the M - the cost associated of retaining a customer - should take into account the cost of encouraging her to talk about your brand and recommend it to others. From this vantage point then, M is more than just the amount that one spends on her directly (i.e., 1to1 channels), but also things like advertising (spillover/tangential or directed to her) and effects of other people on her purchase decisions. Amongst other things.
How do we account for that in GC and in M?
2. Why is it that we don't have a similar measure for media investments?
In media planning, we talk of GRPs, shares of voice, reach, frequency, impressions... and the cost of each (e.g., Cost per GRP, Cost per Reach Point, Cost per Impression). Some more sophisticated companies will measure returns on investments per medium or per level of investment in a certain medium.
But these metrics - cost-efficiencies and ROI - are all essentially a measurement in a point in time - NOW. And much as we should be planning for the issues NOW - the impact of what we do NOW will last way into the FUTURE.
So should we not also be talking about the NPV and FV of media investments whilst we are allocating moneys across different media, different levels, different markets?
One last question...
Why are media companies not talking about these things when they are supposed to be the investment experts?
a friend has this philosophy about the discount season: "sale seasons are designed such that you spend in order to save. hence, i don't wait for them. i buy regardless if it's the discount season or not - as long as i need it and i have the cash to get what i want."
the same is true with marketing: a lot of people are so concerned with ROI - and i mean the numeric ROI that comes after a thorough understanding of the factors that make up the formula (returns/costs). it doesn't matter whether the costs are high or low - so long as they get a "decent", acceptable ROI.
ROI - when misused - is like spending lots in order to get more.
ROI planning is not bad. but it is only one facet of planning that needs to be taken into account. there are more.
(and as an aside, I should say, what really is ROI? my first bosses impressed on me that ROI is not savings, discounts, nor simple calculations. we went into discussions of NPVs, FVs, cashflows, future value of money, internal rate of return, and all that - things i never really mastered [i doubt if i understood them at all] in order to really calculate the ROI. and yes, this was in the marketing department.)
i guess, to each his/her own with regard to measuring ROI.
and i guess that is also where the problems lie.
a focus on ROI can lead to misuse - and disastrous, contradictory - and perhaps, unintended - results.
The Comprehensive R Archive Network I am a believer in making data analytics more accessible to the masses. R is a significant alternative to SPSS, SAS, and other stat software that cost an arm and a leg.