Using Discrete ChoiceModeling to Estimate

Market ShareAdjust 'perfect' test conditions with

real-world assumptions.

By John Golanty

Discrete choice modeling produces "share of choice" output that differs from"share of market" because of assumptions about awareness, distribution, andretention. The author describes strategies for adjusting the underlying assump-tions to fit more realistic scenarios, resulting in reasonable estimates of likelymarket shares for new and established brands.

Marketing researchers' use of dis-crete choice modeling is increas-ing dramatically, as evidenced bythe amount of discussion devotedto the technique at recent indus-

try conferences. Discrete choice models generate"share of brand choices," not "share ol" market,"under a number of different market scenarios. How-ever, as clients become more familiar with choicemodels, they express a desire to interpret the outputin terms of volumetric impact on the business.

Discrete choice modeling is a set of techniquesthat predicts consumers" brand choices given dif-ferent combinations of feature alternatives (such asprice, product, packaging, promotion, etc.) for newor existing brands within a dynamic competitiveenvironment.

Respondents are exposed to different competitivesets in which brands and features are systematically

varied. After viewing each set of options, therespondent selects one brand or none, depending onhis or her most likely purchase behavior if confront-ed in the marketplace with the options presented.

The researcher then analyzes the choices madeacross the varied sets and evaluates the utility of eachoption. Within a competitive scenario, the model canbe used to estitnate share of choices for each brand.It can help evaluate many different scenarios for thetest brand given a static competitive situation as wellas estimate the impact on the test brand if competi-tors were to change their marketing strategies.

MAKING ADJUSTMENTS

It is very important to keep in mind, though, thatthe model's "share of choices" estimate for the testproduct is not the same as brand share in the mar-ketplace. This is because the model assumes the test

MARKETING RESEARCH; FALL 1995, Vol. 7 NO. 4 2 5

Exhibit

Established CPG brand—unadjusted forecast

Sample

Users 50%

Non-users 50

Weighted average

Exhibit 2

Currentshare

50%

0

25%

Rate of awareness/distribution

95%85%

% awareof change

f

11 1 1

2 3 4

months

tJnadjusteddiscretechoice

forecast

60%

10

35%

build

nonusers

T5

100%85%

% distribution

\ \ \2 3 4

months

conditions of 100% immediate awareness, 100%immediate distribution, and user expectations thatare met exactly once the product is tried. To convertdiscrete model shares to market shares, each of theseassumptions must be adjusted to reflect more realis-tic circumstances.

With regard to awareness, there are two effectsto consider: (1) full awareness is almost neverattained, thereby lowering actual market share rela-

tive to share of choices test results, and (2) the rateat which awareness builds also affects market sharerelative to share of choices over a specific, limitedperiod (such as the first year).

If the test brand is a new packaged-goods prod-uct, then we use a separate model to estimate totalbrand awareness that is a function of advertisingweight (adjusted for medium, with TV adjusted forlength, daypart mix, and spot/national mix).

If the brand is an established packaged-goodsproduct, then the media plan/awareness model isused to estimate awareness of the marketingchange among nonusers of the brand. Awarenessamong brand users must be estimated separately ontbe basis of distribution, purchase cycles, mediaplan, and whether the change affects all SKUs oronly some.

In the same way, lack of immediate and full dis-tribution means that some consumers who wouldlike to buy the new or cbanged product cannot doso because it is not available to them. Unlike theshare of choice test environment, the real worldcreates constraints that lower actual market shareestimates. Again, we adjust distribution differentlyfor current brand users (if relevant) because theyare more likely to go to stores where the brand issold and more likely to notice changes on the shelfbecause they already buy the brand.

Manufacturers sometimes commission discretechoice studies before developing a prototype prod-uct. Indeed, these studies are often used to helpdecide which features or changes ought to be con-sidered for incorporation in the prototype. As aresult, respondents are cboosing between optionswithout always baving a good idea about whetherthe selections will turn out to be optimal becausethey haven't had actual experience with the product.The model assumes that users' expectations are metexactly.

Repeat purchase adjustments can be made usingone or more of several options. If the product (orother attribute change) is available, then we recom-mend that it be tested among consumers to see ifactual experience matches pre-usc expectations. Ifproduct testing is not an option, then we must esti-mate the likelihood that expectations will be metbased on results from past research, from categoryaverages, or from educated guesstimates obtainedfrom knowledgeable marketers.

ESTIMATING DEMAND

Here is how the process might work for anestablished packaged-goods brand that is adding aline extension. First assume that .50% of category

26 5, Vol. 7 No. 4 MARKETING RESEARCH:

users buy the existing line, which accounts for 50%of the users' current category volume. Thus, theexisting line has a 25% share of the category (50%penetration x 50% share of requirements).

Assume also that the discrete choice mode! indi-cates the revised line will increase the brand's shareamong current users to 60% and attract 10% of newtriers' volume. Without any adjusttnents, the discretechoice share estimate would be 35% for the revisedline, up from the current 25% level (see Exhibit 1).

However, because awareness and distributionbuild over time, the full impact measured by thediscrete choice model will not be felt immediatelyin the marketplace. If we assume that awarenessand distribution will build as shown in Exhibit 2(estimates based on media plans and distributionexpectations), then market share is likely to be32%, up from 25% (see Exhibit 3).

For users of the existing brand, we are assumingthat distribution for the line extension builds quick-ly to 100% because it will piggyback on the currentproduct. For the year, however, we assume the aver-age distribution for this group will be 90% becauseit takes a few months for distribution to build.

For nonusers of the existing brand, we areassuming that effective distribution reaches 85%(the true All Commodity Volume level) and that itaverages 80% over Year I because of the up-frontbuild. As previously stated, effective distributionfor current users is higher than it is for nonusersbecause the line extension will be placed in storesthat already carry the current brand.

Awareness of the line extension among currentbrand users is estimated to hit 95% because the lineextension will sit on the shelf right next to the cur-rent brand. However, for the year, we estimate thatawareness among current users will average 90%.At the same time, we expect awareness amongnonusers eventually to reach 85% because of astrong marketing plan, but average 75% for theyear because of the slower build.

Combining average awareness and distribution,for users we bave 90% x 90% = 81%. This indi-cates that the unadjusted increase of 10 percentagepoints under conditions of 100% awareness anddistribution is too high and needs to be broughtdown to 81 % of that figure or 8 percentage points.The 8% plus the original 50% yields the 58% fig-ure in Exhibit 3. In the same way, the adjustmentfor nonusers is 80% x 75% x 10% = 6%.

Next, we assume that first repeat purchaseamong new triers will be 50% (a strong repeat fig-ure based on high satisfaction in pre-introductiontaste tests); 50% repeat among 6% who try gener-ates a second purchase among 3% of the original

Exhibit 3

Adjusted for

Sample

Users 50%

Non-users 50

Weighted average

awareness/distribution build

Currentshare

50%

0

25%

UnadjustedD.C.

forecast

60%

10

35%

Awareness/distributionadjustedforecast

58%

6

32%

Exhibit 4

Adjusted forand

Sample

Users 50%

Nonusers 50

Weighted average

Currentshare

50%

0

25%

awareness, distribution,repeat purchases

UnadjustedD,C.

forecast

60%

10

35%

Adjusted forAware/Distr,

58%

6

32%

Adjusted forRepeat

58%

30%

Nonuser Trial, Adjusted forAwareness and Distribution -

1st Repeat Among New Triers - 50%

Add'l Repeats/Repeaters

Total Purchases

Assume Avg CategoryPurchases/Yr

Share From New Users

Purchases/100 NonUsers

6% 6

3

= 3 9

= 10

^ 18/1,000 = 2%

18

1,000

nonusers. culminating in three purchases per 100nonusers (see Exhibit 4).

Assume further that these first time repeaters willbuy the line extension an average of three more titnesduring the year. If 3% buy three more times, this pro-duces nine more purchases per 100 original nonusers.Therefore, total purchases for the line extension willbe 18 purchases per 1(X) original nonusers.

If 100 nonusers of the original brand make an aver-age of 10 categoi"y purchases per year, then 18 out of1,000 purchases indicates a 2% share from these new

MARKETING RESEARCH: FAU 1995, Vol. 7 NO. 4 2 7

John Golanty is ExecutiveVice President,Conway/Mittiken &Associates. Chicago,

triers. It also says that of the 10 purchases in the cate-gory for the average categoiy buyer who tried the lineextension, five purchases will go to the line extension(the trial, first repeat, and thi"ee subsequent purchases.)A 50% share of requirements is reasonable for a newpopular item in its first year. Among users of the cur-rent brand, assume that expectations ai'e met and thatno further adjustment is required.

The.se adjustments lead to a 30% market share esti-mate for the brand, up from the current 25%, but downsubstantially from the discrete choice unadjusted esti-mate of 35%. For new brands, the differences betweenadjusted mai'ket shares and unadjusted choice sharestend to be much greater, leading to lower marketshares and underscoring the need to be cautious wheninterpreting unadjusted discrete choice output.

ASSUME CAREFULLY

As the use of discrete choice modeling prolifer-ates, it is important to keep track of the assump-

tions being made, always asking of the output:"This is .share of what?" The example I have usedhere shows one way to convert share of choices toshare of market.

One major benefit of this approach is that a single-cell discrete choice study can be used in place of amulticell simulated test market study, not only reduc-ing costs but also increasing diagnostic capabilities.For example, unlike most STM systems, the discretechoice approach allows one to simulate the impact ofdefensive competitive reactions on the test product.

For those who conduct in-home use tests, theinclusion of discrete choice exercises both prior toand after placement (testing variables such as price,names, packaging, etc.) would allow one to add astrong forecasting component to the IHUT analysis.

Discrete choice modeling is an exciting tool formarket researchers, providing benefits only dreamedof a decade ago. When used properly, it can be aneffective and efficient way to provide marketingdirection in a very competitive environment. E^

U R K I V O W T . E D G E O E IVIARKETINGXERJMS AND TRENDS!

AMA's newest books will keep you current.

Dictionary of Marketing Terms

Peter D. Bennett, editorPennsylvania State University

This completely revised andexpanded edition is an essentialreference for business

professionals and students alike. Fullycross-referenced for ease of use. thiscomprehensive resource lists more than2500 up-to-date definitions of today's most importantmarketing terms. Covering both the day-to-day terminologyand the specialized vocabulai7 in corporate and academic use.the Dictionary helps everyone from newcomers to senior-levelmarketing executives gain a more thorough understandltig ofcritical mai"keling concepts.

Members/$39.95 Noitmemhers1995.

AMA Marketing EncyclopediaIssues and TrendsShaping the Future

Jeffrey Heilbrunn, editor

W ith an emphasis on recentand emerging i.ssues, apanel of leading marketing

experts surveys the key areas of marketing,identifies cutrent trends, and provides realistic prescriptions forthe future. Contributors include industry leaders and top-nameacademies, as well as pioneers and inventors of key marketingstrategies and techniques: Tony Alcssandra. John Hauser,Philip Crosby. Philip Kotler, Jack Trout, Al Ries, Don E,Schultz, Jagdish Sheth. and many others. The pasl. present,and future of marketing is shaped in this renowned book.

S42AMA Memher/S47.95 Nonmembers1995.

CALL TOLL-FREE 1-8OO-AN1A-115O TO PLACB YOUR ORDER.HAVE YOUR CREDIT CARD AND AMA MEMBERSHIP NtJMBER HANDY. REFER TO MR 125 WHEN YOU CALL.

M E R N I V l A R K E T I T S l i : ; A S S O O I A T I O N2 5 0 S W a c k e r D r i v e S u i t e 2 0 0 C h i c a I t , 6 0 6 0 6 - 5 8

2 8 FAEI 199S, Vol. 7 No. 4 MARKETING RESEARCH: