Zanidip Dirichlet Modelling

Applying the Dirichlet Model to Applying the Dirichlet Model to Forecasting brand GrowthForecasting brand Growth

GP Longitudinal Prescribing in Hypertension Market 2004

Source – Synovate Jigsaw Data for 10 – 15 years

The Dirichlet ModelThe Dirichlet ModelThe Dirichlet model describes patterns of repeat purchases of brands within a product category. It models simultaneously the counts of the number of purchases of each brand over a period of time, so that it describes purchase frequency and brand choice at the same time. It assumes that consumers have an experience of the product category, so that they are not influenced by previous purchase and marketing strategies; for this reason, consumer characteristics and marketing-mix instruments are not included in the model. As the market is assumed to be stationary, these effects are already incorporated in each brand market share which influences other brand performance indexes calculated by the model. The market is also assumed to be unsegmented. The theory and development of the model is fully described in Ehrenberg (1972).

Hyt MS b wAll 100 83.2Istin 5.6 78 6.0Plendil 4.2 47 7.5Nifedipine 2.1 43 4.0Diltizem 1.5 46 2.7Zanidip 1.2 20 5.3

Prescribing for Hypertension



What do you notice about the double jeopardy pattern?

If Istin is ‘about right’ – which others might be ‘about right’ and which others might be exceptional?



What do you notice about the double jeopardy pattern?

Plendil has low b and high w

Nifedipine about right

Diltiazem high penetration and low frequency

Zanidip low penetration and high frequency


Hyt MS b(o) b(t) w(o) w(t)Istin 5.6 78 76 6.0 6.1Plendil 4.2 47 67 7.5 5.2Nifedipine 2.1 43 44 4.0 3.9Diltizem 1.5 46 35 2.7 3.6Zanidip 1.2 20 30 5.3 3.4

Dirichlet gives the benchmarks for the drugs and confirms the analysis – Istin and Nifedipine are in line, Diltiazem is used by more doctors less frequently than predicted and both Plendil and Zanidip have a lower prescriber base than predicted along with a higher frequency – ie. A targetted strategy.

% doctors prescribing:1 2 3 4 5 6 7 8 9+

Plendil O 22 12 6 11 8 7 5 3 28T 27 17 12 9 7 5 4 3 17

Prescribing for Plendil

Fewer than predicted prescribing 3 times or less

Slightly more than predicted at 4-7

10% more of prescribers than predicted are heavy

Prescribing for Zanidip

Many fewer than predicted prescribing 4 times or less

Slightly more than predicted at 4-7

18% more of prescribers than predicted are heavy

% doctors prescribing:1 2 3 4 5 6 7 8 9+

Zanidip O 28 16 10 6 6 4 4 6 22T 42 19 11 7 5 3 3 2 8

Plendil and ZanidipPlendil and Zanidip

• Remove top 10 doctors from Plendil and top 8 from Zanidip:

– Plendil would have a penetration of 43% and a frequency of 5.6 (versus 47% and 7.5)

– Zanidip would have a penetration of 16% and a frequency of 3.5 (versus 20% and 5.3)


So given it’s market share, Plendil is less ‘deviant’ than Zanidip:

Plendil 44% higher frequency than predicted

Zanidip 55% higher frequency than predicted

Is this the result of targeting?


• Factoring up to the population (assuming Jigsaw panel representative) implies that:

• Plendil targeting 1200 GPs• Zanidip targeting 1000 GPs

• Is this right? – if so which doctors are they?


• The top 20 GPs prescribe 27% of the DHPs (equates to 2400 GPs in population

• Plendil prescribed by 70% of these and Zanidip by 45%

• 5 of the top 20 prescribe both drugs


• So Plendil is prescribed by 70% of the top DHP Rxers – but how many of the top Plendil Rxers are in the top 20 DHP Rxers? – answer only 45%

and

• Zanidip is prescribed by 45% of the top DHP Rxers – but how many of the top Plendil Rxers are in the top 20 DHP Rxers? – answer only 25%

Duplication of Prescribing - Duplication of Prescribing - qtrqtr

% rxers of: who also rx:Istin Plendil Nife Dilt Zanidip

Istin 28 26 23 12

Over twice as many Rxers of Istin also prescribe Plendil as Zanidip

So does this mean that there is a group of GPs which rx Istin and Plendil and another which favour Istin and Zanidip?



Istin 28 26 23 12Plendil 44 23 23 11

Looking at Plendil Rxers seems to confirm this ‘segmnentation’.

Four as many Rxers of Plendil also prescribe Istin as Zanidip



Istin 28 26 23 12Plendil 44 23 23 11Nife 55 32 25 9Dilt 57 36 29 15Zanidip 49 30 18 25Ave. Dup. 51 31 23 23 12

The full duplication table shows there is no segmentation – on average about half of the rxers of any brand will also prescribe Istin and just over 10% of the prescribers of any brand will also prescribe Zanidip.


Duplications are in-line with penetrations


Istin 28 26 23 12Plendil 44 23 23 11Nife 55 32 25 9Dilt 57 36 29 15Zanidip 49 30 18 25Av. Dup 51 31 23 23 12Penetration 46 29 21 18 11

2004 – Zanidip % Prescribing Percentage Prescribing (yr)

100%-loyal prescribers mnth

Category Prescribing

quarter Year 1-2 9+ % Rate Rate SCR Observed 11 20 44 22 2.3 1.0 29 9 Theoretical 15 30 61 8 2.1 1.1 31 6 Successfully Diagnoses penetration shortfall light and heavy prescribing bias 100% - loyal prescribing Rates and share of category prescribing

Zanidip Brand Performance Zanidip Brand Performance AuditAudit

DHPs ACEs and AIIsDHPs ACEs and AIIsHyt MS b wAll 100 83.2Tritace 9.9 86 9.6Istin 5.6 78 6.0Cardura 5.6 74 6.2Coversyl 4.9 55 7.4Plendil 4.2 47 7.5Diovan 2.3 41 4.7Amias 2.2 41 4.6Nifedipine 2.1 43 4.0Diltizem 1.5 46 2.7Zanidip 1.2 20 5.3

DHPs ACEs and AIIsDHPs ACEs and AIIs

• No difference in the patterns of prescribing– Istin like Cardura– Diovan and Amias like Nifedipine

• Shows how Plendil and Zanidip are out of line

Objectives for ZanidipObjectives for Zanidip

• 25% share increase + 1.5%• 50% share increase + 1.8%• 100% share increase + 2.4%• 200% share increase + 4.8%

• What are the implications?

Zanidip + 25% market ShareZanidip + 25% market Share

25% grow MS b wZanidip 1.2 20 5.3

all from w 1.5all from b 1.5

Zanidip + 50% market ShareZanidip + 50% market Share



Zanidip + 100% market Zanidip + 100% market ShareShare



Zanidip + 25% market ShareZanidip + 25% market Share25% grow MS b wZanidip 1.2 20 5.3Dirichlet 1.5 34 3.4all from w 1.5 20 6.6all from b 1.5 25 5.3

W=6.6 possible (Plendil) – but normally a 5.6% brand like Cardura

Zanidip + 50% market ShareZanidip + 50% market Share50% grow MS b wZanidip 1.2 20 5.3Dirichlet 1.8 39 3.8all from w 1.8 20 8.0all from b 1.8 30 5.3

Tritace with 10% share has w = 9.6 so 8.0 with a 1.8% drug seems unrealistic.


100% grow MS b wZanidip 1.2 20 5.3Dirichlet 2.4 47 4.2all from w 2.4 20 10.6all from b 2.4 40 5.3

No drug has a w of 10.6!


200% grow MS b wZanidip 1.2 20 5.3Dirichlet 4.8 69 5.8all from w 4.8 20 21.2all from b 4.8 80 5.3

Growth must come from Penetration!

Generalising the findingsGeneralising the findings

• Similar patterns hold in other categories – you have seen evidence (limited) with ACEs and AIIs

• This means we can use the analysis for new brands in existing categories – eg Transtec pre launch

• We can also use the approach to model assumptions about the potential for a new launch to expand usage (eg SSRIs in the Depression category)

• The key outputs are penetration targets which can feed into sales and marketing planning

Some marketing realitiesSome marketing realities

• Attitudes may not predict behaviour• Understanding GPs and what they prescribe is the core of

marketing• Markets change (slowly), but brands continue• GPs often fail to notice differentiation• Brand leaders have the most customers• Brand leaders are bought more frequently• Brand leaders attract higher loyalty

Zanidip Dirichlet Modelling

Documents

Transcript of Zanidip Dirichlet Modelling