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Interaction Between Shelf Layout and Marketing Effectiveness and Its Impact On Optimizing Shelf Arrangements


  • van Nierop, J.E.M.
  • Fok, D.
  • Franses, Ph.H.B.F.


Allocating the proper amount of shelf space to stock keeping units [SKUs] is an increasingly relevant and difficult topic for managers. Shelf space is a scarce resource and it has to be distributed across a larger and larger number of items. It is in particular important because the amount of space allocated to a specific item has a substantial impact on the sales level of that item. This relation between shelf space and sales has been widely documented in the literature. However, besides the amount of space, the exact location of the SKU on the shelf is also an important moderator of sales. At the same time, the effectiveness of marketing instruments of an SKU may also depend on the shelf layout. In practice, retailers recognize that these dependencies exist. However, they often revert to rules of thumb to actually arrange their shelf layout. We propose a new model to optimize shelf arrangements in which we use a complete set of shelf descriptors. The goal of the paper is twofold. First of all, we aim to gain insight into the dependencies of SKU sales and SKU marketing effectiveness on the shelf layout. Second, we use these insights to improve the shelf layout in a practical setting. The basis of our model is a standard sales equation that explains sales from item-specific marketing-effect parameters and intercepts. In a Hierarchical Bayes fashion, we augment this model with a second equation that relates the effect parameters to shelf and SKU descriptors. We estimate the parameters of the two-level model using Bayesian methodology, in particular Gibbs sampling. Next, we optimize the total profit over the shelf arrangement. Using the posterior draws from our Gibbs sampling algorithm, we can generate the probability distribution of sales and profit in the optimization period for any feasible shelf arrangement. To find the optimal shelf arrangement, we use simulated annealing. This heuristic approach has proven to be able to effectively search an enormous solution space. Our results indicate that our model is able to fit and forecast the sales levels quite accurately. Next, when applying the simulated annealing algorithm to the shelf layout, we appear to be able to increase profits for all the stores analyzed. We compare our approach to commonly used shelf optimization rules of thumb. Most sensible rules of thumb also increase expected profits (although not as much as our optimization algorithm). In particular, it is beneficial to put high-margin items close to the beginning of the aisle (or the “racetrack"). Finally, we provide managerial implications and directions for further research.

Suggested Citation

  • van Nierop, J.E.M. & Fok, D. & Franses, Ph.H.B.F., 2006. "Interaction Between Shelf Layout and Marketing Effectiveness and Its Impact On Optimizing Shelf Arrangements," ERIM Report Series Research in Management ERS-2006-013-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  • Handle: RePEc:ems:eureri:7632

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    References listed on IDEAS

    1. Yang, Ming-Hsien & Chen, Wen-Cher, 1999. "A study on shelf space allocation and management," International Journal of Production Economics, Elsevier, vol. 60(1), pages 309-317, April.
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    Cited by:

    1. Erica Herpen & Erjen Nierop & Laurens Sloot, 2012. "The relationship between in-store marketing and observed sales for organic versus fair trade products," Marketing Letters, Springer, vol. 23(1), pages 293-308, March.
    2. Péter Boros & Orsolya Fehér & Zoltán Lakner & Sadegh Niroomand & Béla Vizvári, 2016. "Modeling supermarket re-layout from the owner’s perspective," Annals of Operations Research, Springer, vol. 238(1), pages 27-40, March.
    3. van Nierop, J.E.M. & Leeflang, P.S.H. & Teerling, M.L. & Huizingh, K.R.E., 2011. "The impact of the introduction and use of an informational website on offline customer buying behavior," International Journal of Research in Marketing, Elsevier, vol. 28(2), pages 155-165.
    4. Mou, Shandong & Robb, David J. & DeHoratius, Nicole, 2018. "Retail store operations: Literature review and research directions," European Journal of Operational Research, Elsevier, vol. 265(2), pages 399-422.
    5. Pizzi, Gabriele & Scarpi, Daniele, 2016. "The effect of shelf layout on satisfaction and perceived assortment size: An empirical assessment," Journal of Retailing and Consumer Services, Elsevier, vol. 28(C), pages 67-77.
    6. Hübner, Alexander & Schaal, Kai, 2017. "A shelf-space optimization model when demand is stochastic and space-elastic," Omega, Elsevier, vol. 68(C), pages 139-154.
    7. Zhao, Ju & Zhou, Yong-Wu & Wahab, M.I.M., 2016. "Joint optimization models for shelf display and inventory control considering the impact of spatial relationship on demand," European Journal of Operational Research, Elsevier, vol. 255(3), pages 797-808.
    8. Péter Boros & Orsolya Fehér & Zoltán Lakner & Sadegh Niroomand & Béla Vizvári, 2016. "Modeling supermarket re-layout from the owner’s perspective," Annals of Operations Research, Springer, vol. 238(1), pages 27-40, March.
    9. Sergio Meza & K. Sudhir, 2010. "Do private labels increase retailer bargaining power?," Quantitative Marketing and Economics (QME), Springer, vol. 8(3), pages 333-363, September.
    10. van Everdingen, Yvonne M. & Sloot, Laurens M. & van Nierop, Erjen & Verhoef, Peter C., 2011. "Towards a Further Understanding of the Antecedents of Retailer New Product Adoption," Journal of Retailing, Elsevier, vol. 87(4), pages 579-597.
    11. Bauer, Johannes C. & Kotouc, Alexander J. & Rudolph, Thomas, 2012. "What constitutes a “good assortment†? A scale for measuring consumers' perceptions of an assortment offered in a grocery category," Journal of Retailing and Consumer Services, Elsevier, vol. 19(1), pages 11-26.
    12. Adam, Abdulfatah & Jensen, Jørgen D. & Sommer, Iben & Hansen, Gitte L., 2017. "Does shelf space management intervention have an effect on calorie turnover at supermarkets?," Journal of Retailing and Consumer Services, Elsevier, vol. 34(C), pages 311-318.
    13. Robert P. Rooderkerk & Harald J. van Heerde & Tammo H. A. Bijmolt, 2013. "Optimizing Retail Assortments," Marketing Science, INFORMS, vol. 32(5), pages 699-715, September.

    More about this item


    Hierarchical Bayes; Markov Chain Monte Carlo; Sales Models; Shelf Management; Simulated Annealing;

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing


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