Rebates and Discounts represent one of the largest line items on Financial Statements of Pharmaceutical Manufacturers, yet the criteria for assessing contracting decisions often lacks the analytical rigor that match the financial exposure. Pre-deal analysis uses inputs from account managers which tend to overestimate both the benefit of contracting and the risks associated of not contracting. This is not a surprise since factors beyond Pharma’s control can impact the actual results, including a payer’s formulary control and related spillover impacts.

The ability to control costs and enforce formulary compliance differs across healthplans, often based on size, geographic location, competition, internal policies & procedures, etc. More controlling payers (i.e. Kaiser) have strong internal policies and operate in a somewhat defined geography. Payers exerting less control tend to operate on a national basis with numerous sub-plans. This diversity provides more opportunity for local factors to influence processes and is exhibited in the variability of formulary compliance in downstream entities of large plans and PBMs. Pharma needs to recognize these variations and use analytical models to support negotiation strategies that maximize product performance.

Further a payer’s ability to effectively control and enforce its formulary may vary by therapeutic area (TA). Therefore, factors used to make a contracting decision for one TA may not be applicable across a Pharma company’s portfolio.

Closing the Gap through Analytics & Insight

In order to effectively implement a successful contracting strategy Pharma needs analytical tools to address several key questions related to market conditions and related variables.  These include quantifying a payer’s ability to enforce controls on prescribing, assessing a product’s forecasted performance at higher vs. lower co-pay levels, and measuring the effectiveness of a well-designed co-pay card program.  Insights resulting from this analysis can directly influence contracting decisions including terms, rebate levels, tier placement, etc.

Axtria Inc.

As the marketplace continues to evolve, the need to support key business decisions through analytics has become much more than a “nice-to-have”; it is a business requirement.  Axtria is an advanced analytics company that combines industry knowledge, analytics and technology to deliver solutions that help companies make better data-driven sales, marketing and Managed Markets decisions, with measurable results.  Axtria has the experience to develop data- & analytically-based operational processes for managed markets that not only deliver a ‘what happened’ answer, but also create a foundation for answering the thornier questions of ‘what should we do next?’.  Additional insights on this topic are available in a whitepaper which can be requested at http://axtria.com/insights/whitepapers/

About the Author

Mike is an experienced leader in the Pharmaceutical industry with extensive background and expertise in streamlining operations, developing insightful analytics and building strategies for new and existing markets.  He has over 25 years of experience in the Industry, a majority of which focuses on leadership roles in Managed Markets and Commercial Operations.  Mike holds an MBA from the Lubin School of Business, Pace University with a concentration in Management Information Systems. He holds a Bachelors in Business Administration from Siena College in Albany N.Y. To learn more about Michael click here

Given where the market is today and where it is heading, this makes no sense.

Arguably the most dynamic customer segment within the bio-pharmaceutical industry today is managed markets.  From ‘traditional’ merger and acquisition activity to ‘transformational’ consolidation (e.g., Aetna’s acquisition of Medicare Advantage & Part D leader Coventry Health Care) to ‘vertical integration’ by integrated health groups/systems, dramatic change has happened already.  While there is much uncertainty in the overall direction of the US healthcare market from a macro policy and political perspective, the ‘certainties’ for bio-pharmaceutical organizations are these:

• the emphasis on cost control will only increase
• the relative impact of the sales force on results will decrease
• the need for innovative managed markets strategies will increase

However, because of the history of under-investment, many managed markets operations and analytical teams face numerous challenges beyond the considerable number of market and competitive factors, such as:

• Sub-optimal customer master databases:
  • Incomplete current representation of the market (e.g., parent-child relationships)
  • Lack of comprehensive “bridge” files to map across differing internal and external data sources
  • Insufficient business process and tools to update changing data over time
• Lack of a well-defined and organizationally-agreed-upon set of KPIs to drive
  • Account management
  • Account planning
  • Resourcing decisions
  • Incentive compensation
• Over-reliance on Key Account Managers (KAMs) for anecdotal local-market data and account insights versus ‘owning’ a corporate data asset that captures and leverages these data
• … and more

It doesn’t have to be this way.  In this blog series, Axtria will lay out business practices that can allow you to bridge a variety of third party data sources with structured insight from your KAMs (“Key Account Managers”) to develop data- & analytically-based operational processes for managed markets account teams, approaches that not only deliver a ‘what happened’ answer, but also create a foundation for answering the thornier questions of ‘what should we do next?’.

Want to stay ahead of the competition? Contact the author.

About the Author:

Patrick Brundage is a Principal at Axtria focused on bringing best-in-breed commercial analytics solutions to customers across multiple industries including life sciences, healthcare technology and insurance. Patrick has focused exclusively on working with organizations to improve the productivity of their sales and marketing strategies and tactics through advanced analytics. His passion lies in bringing a disciplined and scientific approach towards sales and marketing to help client companies maximize their product and market performance. To learn more about Patrick click here.

Axtria is an advanced analytics company that combines industry knowledge, analytics and technology to deliver solutions that help companies make better data-driven sales and marketing decisions, with measurable results.

Dhananjay is a Principal at Axtria India Office with a focus on strengthening Axtria’s DWBI practice and IT services across industry verticals. He has over 20 years experience in the industry which includes over 12 years of experience in DW, BI and Analytics. Prior to joining Axtria, he was an AVP with Mahindra Satyam focusing on BIDW and Analytics horizontal for North America. During his experience of over 10 years at Mahindra Satyam & Satyam, he has led multiple transformational BIDW programs with top US based companies. He has also worked with other companies like UnitedHealth Group and PwC.

Dhananjay has extensive experience in leading and implementing Information Management programs in Manufacturing, Financial Services and Healthcare verticals. Dhananjay spends his time researching the future of technologies in the area of Information Management and believes that quick adoption and harnessing them for competitive advantage will make enterprises future ready.

Dhananjay is an engineering graduate from IIT Kharagpur and holds a Master’s Degree in Business Management from the same institute.

April 15 marks an important, but frequently overlooked “forward inflection point” in the annual cadence for marketing and sales organizations.

Sure, the taxes are due.  But for sales strategy and operations teams, April 15 is ~ 100 days into the new year AND ~ 100 days from the beginning of the 2014 budget planning process (uggh, already ? ).

As with filing our taxes, the April 15 milestone is marked by:

• Close the books on the prior year
• Measure what worked, what didn’t work
• Consider strategies for current (tax) year and beyond
• Pay your taxes (…or collect a refund).

On the measurement front, a proactive Sales Strategy & Operations group will mark the April 15 occasion to measure and learn.  The annual budgeting process is likely to commence in the next 90-120 days and you will want to be armed with quantified results to inform that process.  For instance, did your sales organization …

• … Implement some pilot programs in 2012 ?  Measure them and be ready with scale / stop recommendations.
• … Realign the territories at year end ?  Your sales force should be well through the ‘disruption’ phase and gaining significant traction.  Who is lagging ?  What customers remain under-covered ?
• … Implement new (training / technology / messaging … fill in the blank) programs ?   Measure the incremental sales and ROI, and be ready with scale / stop recommendation for each program.

More strategically, when is the last time you took a hard look at your sales force size ?  Right now is the perfect time to raise that question and consider whether or not to evaluate your sales force size.  The marketplace changes every day, has your sales force size and structure kept up ?  Product lifecycle, new products, new competitors, financial considerations, etc. all have an impact on the value your sales force generates.

The second quarter is the perfect time to analyze and critically evaluate your sales and marketing investments so that you are ahead of the annual budget planning process.  Be sure to know what to keep, cut, defend and reallocate.

Strategically, Axtria can help you evaluate your sales force size.  The next blog posting in the Sales Strategy and Ops series will cover the Six Classic Sales Force Sizing Approaches.  Happy to compare notes with you to determine if you need a (continuing with the tax metaphor here) 1040EZ, 1040 full form, or complete audit of your sales force investment.

Tactically, the Axtria team is great at measuring sales and marketing program ROI (topic for another day / series).

Remember, if you are in Sales Strategy & Operations, you are already working too damned hard (your taxes on top of 1Q incentive compensation payout calculations …).We can help.

Over the past several decades, we have experienced a proliferation of channels, including direct sales, mass media advertising (think Mad Men), direct mail, telesales, online/digital, email, social, mobile etc. Each of these channels has advantages with respect to efficiency or effectiveness (topic for another day), often work well in combination, and should be tailored to the chosen business and marketing strategy.

Let’s spend a minute to clarify some semantics that may be helpful:

For many years, we have used iterations of the following framework (affectionately called the ‘octopus’) to help bring ‘order to chaos’ in helping clients define their go-to-market strategy for the sales organization.  (By the way, we assume product, value proposition, marketing strategy have been already decided).  The framework simplifies the sales organization’s GTM Gordian knot into a few simple questions:

1. What customers  do we serve ?
2. What work needs to be done ?
3. How should we approach the market ?

Let’s explore each of these major questions a bit more.  For those of you familiar with the Axtria team, you’ll know that we take a very data-driven, quantitative approach to these questions.

What Customers to Serve ? 

The essence of this question is a clear definition of the customer universe coupled with a  good customer segmentation scheme.

Customer universe:  pardon the pun, but sometimes you must scour the universe for a reliable data source for a customer universe.  Some war stories that delivered break-through value include:

• Cold calling the National Institutes of Health for a database of NIH research award recipients for a European laboratory equipment manufacturer looking to enter the U.S. market
• Appending a B2B client’s entire customer database of 2.5 million active accounts with the D&B’s data to identify which 10 million US businesses were NOT active customers
• Licensing a national database of 120 million US households, appending 20 million in-force customers for a Fortune 500 insurance company, in order to develop a comprehensive customer & prospect master
• Creating physician or hospital level databases too numerous to count, in order to support the commercial operations of life sciences companies with sales forces from 4 to 12,000 sales people.
• Click here to share a war story

Customer segmentation:  since not all prospects and customers are created equally, you must segment based on needs, behavior, profile attributes, potential, etc.  We will discuss segmentation in other blog postings and CustomerIQ. Segmentation for sales strategy purposes should consider factors such as:

• Market potential sufficient for investment of direct sales effort
• Buying needs that must be addressed by direct sales
• Overlap of purchases

Targeting & Reach:  coverage decisions must be based on the ability to deliver the needed work at a profit to a given customer segment.  We’ll cover this in much greater detail in sales force sizing postings.

What essential work must be done to serve customers ? 

Customer segments will have various needs from a direct sales channel.  As a rule, one should seek to deliver services by the lowest cost channel(s) that will differentiate yourself from competitors while satisfying the customer need.

For example, selling to a hospital or factory floor often involves (at least) two very different but essential work types:

• Carpeted floor – the ‘business’ sale to financial and contracting gatekeepers
• Tiled floor – the ‘technical’ sale to users

Both must be addressed in sequence or in parallel, one-time or continuously.  In addition, you will want to estimate the amount of work needed to penetrate and provide ongoing sales coverage to each customer segment type.

How to approach the market ?

In addition, consider the selling roles needed to deliver the work to the customer segments.   At Axtria, we prefer to do the customer universe and essential work legs FIRST.  This ‘data’ provides insight to the roles that you should consider.  We frequently see harried sales strategy & operations teams take the shortcut to only consider conventional selling roles (hunter, farmer) and miss innovative opportunities (clinical informatics consultant, auto retail consultant) that win clients’ hearts and bedevil competitors.

As you click these items together (What customers ? What work ?  What roles ?), they become a single go-to-market (“GTM”) scenario with quantifiable outputs such as number of customers reached, sales resources required by role, total cost of sales, revenues generated by the sales resources, and incremental profits.  In developing a go-to-market strategy, literally hundreds of scenarios may be evaluated and then optimized.  We’ll discuss more of this evaluation + optimization process in future blog posts.

What additional questions do you feel are essential for a sales organization’s GTM strategy ?

Does your go-to-market strategy answer these questions ?   or do you have new, unanswered questions ?

Please contact us here to compare notes, we’d love to learn more about your business.

1) Conference Tutorial: Axtria’s principals, David Wood and Patrick Brundage, will be driving the first tutorial session of the conference on May 5, 2013 covering introductory, intermediate and a few advanced topics in Pharmaceutical Promotion Response.

Starting from the basics of ROI, test and control methods the session would elevate to the next level covering response curve (regression-based) methods, will examine physician segmentation for response, alternative response model mathematical forms, and optimization criteria. The session also includes hands-on exercises consisting of basic fitting of models (in Excel) using prepared data, and discussion / interpretation of the estimated coefficients. Advanced topics to be discussed include threshold effects in response curves (“S-shaped response curves”) and multi-channel models, with and without interaction effects. The session will prove to be a complete journey into the pharmaceutical promotion response world.

2) PMSA Podium Presentation: Patrick Brundage will also be presenting on May 8, 2013 introducing “A Market-Driven Model for Managed Markets Alignments”, an approach that not only delivers an ‘alignment answer,’ but also creates a foundation for ongoing data management, reporting and resource optimization.

3) Poster Presentation: David Wood will represent Axtria in this year’s PMSA poster presentation on AHP and Simulation for Clinical Development Prioritization.

PMSA is a not for profit organization with a mission to efficiently meet society’s pharmaceutical needs through the use of management science. Learn more about PMSA and the conference by following the link below:

http://www.pmsa.net/

Cherry picking

Studies have shown that heavy discounts not only lead to cultivation of cherry picking behaviour among consumers, but also lead to brand dilution. When consumers are trained to cherry pick, they lose the loyalty that they otherwise have towards the brands. It is, therefore, very important for brand managers to have a long term strategy towards discounting rather than resorting to short term gimmicks, which result in a one-time spike in sales and also in heavy switching behaviour among consumers.

I will quote an example to prove my point. My wife and I visit a certain modern retail store in our vicinity, where there is usually a promotion running on Basmati rice, on a daily basis. Now, given that there are around 8 – 10 popular mainstream brands of Basmati rice, which have almost the same quality (I can vouch for that as I have consumed most of them by now) that are always on discount, it is a natural instinct on our part to buy the one which affords the best value for money. Now, among these brands, there is a brand which we used to like and bought it regularly, before this circus of discounting started. But ever since then, we have not bought this particular brand even once out of brand loyalty (and if I look at our basket over a six-month period, it has found its way into our basket only once, and that too when it was on promotion). This proves a very pertinent point; that a haphazard, short term promotional policy is hurting the brand. We are no longer inclined to pick up this brand as it doesn’t afford us a competitive discount. We have been trained to pick Basmati rice on discount only.

This concept works best for products that have a shorter purchase cycle, but it has also worked wonders for companies which have been able to build a brand loyalty towards them. The best example is that of Apple – once an Apple customer, you are always an Apple customer.

Long term solution

Now, what we have stated above is a problem. Is there a solution at hand? Well, the resounding answer to that is a big YES. What brands need to do is to embark on a long term strategy for promotion, where they help consumers save money by giving them regular offers over a sustained period of time and at a personalised level, so that a loyal consumer knows that he has an exclusive offer for himself, which is the reward that the brand is bestowing upon him for staying loyal to the brand.

The best example of this strategy is the success of a retailer like Tesco, versus a big, everyday discounter like Walmart. Tesco concentrated on growing its base of loyal customers, giving them personalised discounts, based on their buying behaviour, so that customers kept coming back to their store to buy one more product one more time. This helped them to become the top retailer in U.K. accounting for close to a third of the market share in the country. Personalised offers are in the nature of discounts, which are provided to customers, but are unique to the customer and make them feel special as the retailer takes the effort to understand what they buy. Such is the success of the Tesco personalised offer program, that customers have been known to have called up Tesco if they did not get their quarterly mailer (with discounts and offers) in time.

Loyalty pays

But how does a brand identify a loyal customer? This is where partnership with retailers is very important as retailers would have information regarding customers and what they buy. Having information on customers and what they buy is of no use, if it is not acted upon. However, customers have to be incentivised to sign up to a loyalty program and then use the card number repeatedly in their transactions so that they keep adding points to get more relevant offers. Many retailers in the west have special discounts on customers’ first couple of purchases, if they sign up for a card and this get’s them to sign up for the card and start using the same. In today’s age, one is no longer required to carry the card physically, but storing the card number in your mobile phone and quoting the same at the cash counter at the time of check-out ensures that your points are added and your buying behaviour is recorded which helps the retailers to better customise the offers.

The manufacturer has to partner with the retailers to provide the discounts and offers as the information on consumers will be available with the retailers. It is a symbiotic relationship as the retailer gains increased customer footfalls and more instances of customers coming back to the store, while the manufacturer benefits from repeat purchases of their brand. The manufacturer is also clearly able to quantify the ROI (return on investment) on these campaigns by recording the percentage of people who use the discounts and offers, as compared to the total number of people who were sent the offers. Targeted offers through regular mailings have seen very high double digit response rates, whereas traditional one-time campaigns only see single digit responses.

Embedding analytics

The vacuum that exists in the Indian market today is not the absence of fancied loyalty programs, but the absence of well designed analytics-based loyalty strategies that can be used effectively. The other important missing medium is a communication channel. Not many retailers in India seem to have heard or read about Tesco Club Cards and how a now legendary personality called Sir Terry Leahy, made an important decision to invite a little known company called Dunnhumby, to embed analytics and the ethos of a customer first philosophy, which turned Tesco from a unfashionable home grown super market chain to a global retail powerhouse. The irony is that some people would have read and heard about Tesco Club Cards, which is why we have these slew of loyalty programs run by retailers in the country, but not gone deep and understood the science behind how club cards was used to understand customers and build customer loyalty towards Tesco.

The Indian retail Industry, or more specifically modern retail, needs to take that leap of faith and embark on a journey to build customer loyalty towards themselves and also towards the brands that they sell, on behalf of the manufacturers. The Indian manufacturers and brand owners in turn, need to demand this of the retailers and on their part, also help the retailers on this journey by investing generously in building customer loyalty, by espousing the cause of targeted and personalised promotions on a sustained and long term basis. This will help stem the present rot of large scale and mindless discounting, which is hurting the brands and also the customers. Successful partnerships between retailers and manufacturers abound in the west, the most notable ones being between Tesco and its suppliers in the U.K., between Kroger and its suppliers in the U.S.

Market structure

There is an interesting concept in marketing sciences called market structures (and I have had the good fortune of working closely with the only surviving founder of Hendry Market Structures), which uses data on switching behaviour of customers to come up with (amongst many other important solutions) a hierarchy/tree containing the attributes of a product which help a consumer determine which product they would buy when they visit a store/make a purchasing decision. For example, when a consumer buys an ice-cream, what is the first thing that plays on in the mind of a consumer – is it the flavour, the brand or the manufacturer that is his first decision-making point in the tree? For most products, it has been seen that either the brand or the manufacturer, or the category is at the top of the market structure, with other product attributes following at a later stage in the decision making process. My fear is that if we were to do a market structure study across products and categories in the Indian market – neither the brand nor the manufacturer will feature on the top of the decision-making tree in the minds of consumers for a majority of them. This should ring alarm bells for brand managers and manufacturers, as after all, crores of rupees are spent on advertising and promotions to strengthen those very brands, which are now being diluted through discounting. Market structure is a very powerful tool in the hands of brand owners and manufacturers and allows them to understand how products best compete with each other and where opportunities for new products exist; my apologies to all the learned students and teachers of this science for oversimplifying the concept for my example above.

I forgot to mention that I would still love to buy that brand of Basmati rice – the brand should take note before it is too late.

About the Author:

Snehamoy Mukherjee is a part of the strategic leadership team at Axtria, he is responsible for business development, solution development, delivery leadership and strategy formulation. Prior to this, he used to head the analytics practice at Technopak Advisors and has over a decade of experience in the analytics industry having worked in multiple domains like retail consulting, FMCG/CPG, insurance and market research. To learn more about Snehamoy click here

Snehamoy is a frequent contributor to the The Smart CEO magazine. Some of his latest publications can be accessed at http://www.thesmartceo.in/

Axtria is an advanced analytics company that combines industry knowledge, analytics and technology to deliver solutions that help companies make better data-driven sales and marketing decisions, with measurable results.

Several of us here at Axtria have spent much of the last two decades working with sales operations teams across many industries and in dozens of countries.  Our hats go off to you … you are some of the most dedicated, hard-working and underpaid professionals in business.

While there may be no ‘typical’ sales organization or sales operations team, we have noticed a definite cadence to the sales ops year.    True veterans know that Memorial Day marks the pre-budget planning window, Labor Day is the beginning of the year-end sprint, Thanksgiving is just an afternoon off, and holiday shopping can wait until after December 20^th when files for 1/1 get shipped to vendors.

The blog series will follow the ‘typical’ sales operations seasons depicted in the graph below.  Months of the year are along the x-axis and the workload for the sales ops team is on the y-axis.  We assume that the sales force ‘year beginning’ is January 1.

As you can see, there are several key features to the ‘typical’ cadence:

1. Unending work managing customer/sales data and reporting …
2. … plus, dealing with (equally constant) emergencies
3. Planning season in spring that precedes the annual operating budget cycle.  This planning season is typically marked by evaluating the sales force size, structure, and effort allocation
4. Beginning Labor Day, the unrelenting rush for the 1/1 year beginning, when everything needs to be synchronized for the new year.  Major work items include territory realignments, incentive plan adjustments, goal setting, preparation for the year beginning, and so on.

As part of this blog series, we will point out global ‘best practices’, common pitfalls, and ‘pressure relief valves’ that world-class sales operations teams use to manage the overwhelming workload.

In the meantime, if you are in sales ops and feel you’re working too damn hard, contact us here to compare notes.   I bet we’ve seen or felt your pain and would be delighted to help.

Aman is a Principal with Axtria. He has over 14 years of experience across analytics and management consulting. In his career, he has built 2 analytics units from scratch and scaled them to multi-million dollar business lines. His specific area of focus has been Risk, Marketing and Operations Analytics for Banking and Financial Services clients.

Most recently, he was President and Angel Investor at CoCubes Technologies Pvt. Ltd, an online / mobile startup in education space focused on India market. He scaled the business to 100+ team with  5X growth in revenue over 2 years.

Prior to that, he was with Ocwen Financial, as Head of Quantitative Analytics. There he ran a $20 Mn servicing technology and loss mitigation product lines. He was also instrumental in building a decisioning engine to significantly enhance loan modification program, MSR pricing and investment fund performance using advanced statistical, econometric and stochastic modeling methodologies.

Prior to Ocwen, he was one of the key leaders to build out and scale up Analytics Services practice at Inductis Inc. to 200 data scientists.

Aman did his B.Tech from Indian Institute of Technology Kharagpur and MBA from Indian Institute of Management, Ahmedabad.

Before venturing into business models, let us first classify different segments of people on Twitter. We will call them ‘Twitterites’ (for lack of a better word). Now, here is what I think (if Jack Dorsey of Twitter allows me to analyse his data, I can check these hypotheses) are the segments which exist.

The first segment and the one with the maximum amount of followers (number of followers is an important dimension on which I have done the segmentation) is the Twitterati (celebrities with thousands of followers). Now, here is a ratio, which I call into use, called the Stability Ratio – the ratio of number of people you follow divided by the number of followers you have (Stability = You Follow/Your Followers). The Twitterati has a skewed ratio, where the number of followers far outnumbers the number of people that they follow. They are the people whose tweets are also read (theoretically) by a large number of people. Now, having a large number of followers is not enough; one should be active on the Twitter circuit – a tweet a day is a powerful engagement tool. So, the Influence Index = {(number of tweets * number of re-tweets by followers)/number of days in the period under consideration)} would be another interesting ratio to look at to determine who has the strongest impact on the Twitter universe. One can complicate matters to quantify influence further by adding dimensions like reach etc., but we will not go down the path as it will make this otherwise interesting topic look more like a geeky technical paper and invite patent infringement lawsuits from Klout (a US-based company that measures a user’s influence across the social network).

Celebrity power

Twitterati is the segment that brands and people, who traditionally advertise in mass media, will soon start utilising to send out brand messages through their tweets. The branding and messaging need to be subtle, else Twitter will get reduced to a television channel where people will selectively not read tweets that are advertisements. For instance, Amitabh Bachchan would tweet “T9000 I am in Hilton, Ahmedabad – wonderful experience! Meeting fans at the opening of the Brio bar at Hilton & releasing Anupam Kher’s book.”

Now, Hilton pays for the tweet, Gujarat Tourism pays for the tweet and Kher’s publishers pay for the tweet. Three brands propagated with one tweet! This will give birth to a new generation of super copywriters, who would compose tweets for brand ambassadors. The tweets would also differ from day to day but provide the same underlying message, unlike television ads, which run the same ones for months. This is where the tweet ads will change the existing rules of advertising. For instance, using the Amitabh Bachchan example above, the subsequent tweet on the next day could go something like this, “T 9001 The best thing about Hilton is Hilton – my realisation after reading Anupam’s book! At Mandvi beach today – virgin and picturesque.”

I dream of opening a new agency for Twitter advertising/marketing as a self-owned venture some day. I promise nothing but success for advertisers. It will be game changing, personalised and real. The mindless spends on making eye catching videos will come to an end and the monopoly of television ads will slowly but surely come to an end. You will pay per follower that a Twitterite has. People with exceptional talent for Précis writing (you need to adhere to the word limit on Twitter) will be hired.

While on the subject of stability, I maybe accused of inverting the ratio on purpose, to show instability of the Twitterati, based on some long lasting grouse of having never made it big in the show business. But Amitabh Bachchan has a stability ratio of 0.000115, Huffington Post has a stability ratio of 0.002811 and Deepak Chopra’s is 0.003224. Just like cyber squatters, there are Twitter squatters. Even a fake Bill Clinton handle has a stability of 0.001187. So, lower the stability ratio, the more popular a Twitterati is and brands would look to utilise them in campaigns.

Cashing in

The next segment can be called the ‘Followers’ – they have a very high stability ratio, very few followers, but follow a large number of people. Now, we all know that managing to follow even 100 people is difficult on Twitter, especially if they are compulsive Twitter users. But this band of followers will follow people with zeal and passion. A lot of them are excellent readers, who have a lot of patience. Most of them are looking to connect with the rich and the famous, eagerly waiting to gain the bragging rights on tweets and sharing them at table conversations. Brands would love followers to grow as they would be their largest audience for their ad campaigns through the Twitterati.

Twitter needs to divide the Twitterati segment into further sub-segments, which can be aptly named as ‘Super Premium’, ‘Premium’ and ‘Valuable’, and price the marketing campaigns accordingly. The pricing would also be scientific, based on pure numbers and not vague valuations. An added service that Twitter could provide is to gauge the conversations of the followers to find their interest areas and to provide the top interest areas for followers of prospective brand ambassadors (or Twitterati), so that prospective marketers can choose their brand ambassador based on this additional information on the interests of the followers. So, if the majority of the followers of a journalist are interested in health, then health-related products can be marketed through this journalist. Or if a significant portion of the followers show a keen interest in travel, hotels could use them in their campaigns.

The world of Twitter will also throw up very interesting candidates for brand ambassadors beyond our traditional repertoire of film stars, celebrities, sportspersons etc. There would be local school teachers, principals of schools, intellectuals, journalists, socialites etc., who would have a great impact on a catchment area and who could be co-brand ambassadors with the actual brand ambassadors.

Making it count

Sharing revenue from advertising with Twitter users can be an interesting proposition for Twitter to make campaigns go viral and hence, charge a premium for such campaigns. If a Twitter user takes part in a RT (re-tweet) campaign, he/she gets 0.1 dollar per RT of a campaign. This will completely turn the advertising campaign model on its head. Depending on the target number of unique RT’s that a client aspires for, it pays a fee of 0.1 + 0.1 = 0.2 dollars. Half of it goes to Twitter and the other half to each Twitter user. If there are 10 RTs that a Twitter user is able to do for different campaigns, he earns US $1. The number of people that the RT reaches in a certain campaign period will be multiplied to provide Twitter its revenue share. Thus, assuming that on an average, a RT reaches 10 people and there are 0.1 million RTs, then Twitter earns a million dollars per campaign. If it does 1000 campaigns in a year, it will do a cool US $1 billion dollars in revenue. Now, there is some policing required to restrict misuse of RTs. Every person will be allowed one RT per campaign. Only people who have been active on Twitter for at least two months prior to a campaign will be eligible to earn money through RTs. This will ensure more engagement from people on Twitter. Twitter will also have to restrict the number of handles people can create from a single IP – preferably only one handle from a single IP.  The list can go on, but we need to stop somewhere.

I look forward to hearing from Jack Dorsey soon!

About the Author:

Snehamoy Mukherjee is a part of the strategic leadership team at Axtria, he is responsible for business development, solution development, delivery leadership and strategy formulation. Prior to this, he used to head the analytics practice at Technopak Advisors and has over a decade of experience in the analytics industry having worked in multiple domains like retail consulting, FMCG/CPG, insurance and market research. To learn more about Snehamoy click here

Snehamoy is a frequent contributor to the The Smart CEO magazine. Some of his latest publications can be accessed at http://www.thesmartceo.in/

Axtria is an advanced analytics company that combines industry knowledge, analytics and technology to deliver solutions that help companies make better data-driven sales and marketing decisions, with measurable results.