In that case you can create a variable which gives a percentage of Yes over Yes+No: See whether this works for you (assume your data is sample).
mytab <- xtabs((100*Sold/(Sold+Unsold))~Label1+Label2+Label3, data=sample)
> mytab
, , Label3 = CLM_FREE_INCDT_CT: 0
Label2
Label1 CLM_FREE_INCDT_CT: 0 FULL_CVG_FLG: N FULL_CVG_FLG: Y HSEHLD_INCDT_BAND: 0 PRIOR_BI: High SingleMulti: N
AdvancedShopper: Y 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
Channel: Owned Agency 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
Channel: Prudent 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
HSEHLD_INCDT_BAND: 0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
SingleMulti: N 0.000000 0.000000 0.000000 9.694644 0.000000 0.000000
TERR_USED: Non-TREE 0.000000 0.000000 0.000000 9.264615 0.000000 0.000000
Label2
Label1 TERR_USED: Non-TREE
AdvancedShopper: Y 0.000000
Channel: Owned Agency 0.000000
Channel: Prudent 0.000000
HSEHLD_INCDT_BAND: 0 0.000000
SingleMulti: N 0.000000
TERR_USED: Non-TREE 0.000000
, , Label3 = SPINOFF: N
Label2
Label1 CLM_FREE_INCDT_CT: 0 FULL_CVG_FLG: N FULL_CVG_FLG: Y HSEHLD_INCDT_BAND: 0 PRIOR_BI: High SingleMulti: N
AdvancedShopper: Y 8.017762 0.000000 0.000000 0.000000 0.000000 0.000000
Channel: Owned Agency 0.000000 0.000000 0.000000 0.000000 0.000000 9.486133
Channel: Prudent 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
HSEHLD_INCDT_BAND: 0 8.182253 0.000000 0.000000 0.000000 0.000000 0.000000
SingleMulti: N 10.321407 0.000000 0.000000 0.000000 0.000000 0.000000
TERR_USED: Non-TREE 10.202528 10.938276 11.593311 8.472419 10.507445 0.000000
Label2
Label1 TERR_USED: Non-TREE
AdvancedShopper: Y 9.398284
Channel: Owned Agency 9.810104
Channel: Prudent 13.010717
HSEHLD_INCDT_BAND: 0 0.000000
SingleMulti: N 11.881553
TERR_USED: Non-TREE 0.000000
Call: xtabs(formula = (100 * Sold/(Sold + Unsold)) ~ Label1 + Label2 +
Label3, data = l)
Number of cases in table: 150.7815
Number of factors: 3
Test for independence of all factors:
Chisq = 412.2, df = 71, p-value = 1.48e-49
Chi-squared approximation may be incorrect