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In pursuit of an effective B2B digital marketing strategy in an emerging market

Abstract

In business markets, firms operating in developing economies deal with burgeoning use of the internet, new electronic purchase methods, and a wide range of social media and online sales platforms. However, marketers are unclear about the pattern of influence of firm-initiated (i.e., paid media, owned media, and digital inbound marketing) and market-initiated (i.e., earned social media and organic search) digital communications on B2B sales and customer acquisition. We develop and test a model of digital echoverse in an emerging market B2B context, using vector autoregressive modeling to analyze a unique 132-week dataset from a Brazilian hub firm operating in the marketplace. We find empirical evidence supporting our conceptual framework in emerging markets. Underscoring the importance of a market development approach for emerging markets, the findings show that owned media and digital inbound marketing play a bigger role in influencing customer acquisition. Impressions generated through earned social media complement owned media, but not paid media. These insights highlight the notion that while sources of digital echoverse may remain the same across countries, its components exert a particular pattern of influence in an emerging market context. This is expected to encourage managers to rethink their digital strategies for B2B customer acquisition and sales enhancement while operating in emerging markets.

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Notes

  1. We note that O-I-E-O ordering does not imply directionality. We thank an anonymous reviewer for this point.

  2. Notably, social media environment varies between countries. For example, LinkedIn, a widely used social media platform for B2B marketers in the U.S. (154 million users), is still growing in our emerging market context, i.e., Brazil (35 million users). LinkedIn was launched in Brazil in 2010. In terms of utilization, 43% of LinkedIn’s traffic comes in from the U.S. alone. On the other hand, in terms of Facebook membership, the U.S. is the only developed country in the top five list (the rest are India, Brazil, Indonesia, and Mexico). Also, Brazil is the third country in the world based on number of Instagram users (U.S. =120 million, India = 75 million, and Brazil =69 million; Statista 2019).

  3. We thank the reviewer for suggesting the estimation of alternative multiplicative models.

  4. We compared media spending (digital inbound marketing and paid media) ratios over the years (2014–2017) and found inconsistent spending patterns with the elasticities found. Average overall spending on digital inbound marketing is 66.66% against 33.33% on paid media. Given the cumulative elasticities provided and the increasing pattern of digital inbound marketing (e.g., Table 5), managers of the company should reallocate media investments to better adjust to the O-I-E-O sequence. We thank the Guest Editor for this recommendation.

  5. We thank the anonymous reviewer for this recommendation.

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Correspondence to Valter Afonso Vieira.

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Eric Fang and Shrihari Sridhar served as special issue guest editors for this article.

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Appendices

Appendix 1

Table 8 Test for the VARX model dimension and Lagrange-multiplier test for autocorrelation of the fitted VARX model

Appendix 2

Table 9 Unit root and structural breaks routines on model variables in levels and logs

Appendix 3

Table 10 Root Mean Square Error (RMSE) of simulated out-of-sample forecasts: testing VAR improvement against alternative methods

Appendix 4: Forecast error variance decompositions (FEVDs) of inbound marketing and owned media on new sales and customer acquisition

Fig. 6
figure 6

a-d The solid blue line is the resulting FEVD of the simulations due to different VARX orderings considering eight steps (weeks) ahead. The dashed lines show 90% confidence intervals

Appendix 5: Assumptions and potential limitations of (alternative) multiplicative models

As multiplicative regression models are nonlinear in parameters, to linearize, we used a logarithmic transformation resulting in a double-log format. These are widely used in marketing response models as the estimated betas can retrieve the elasticities of marketing performance (here, new B2B sales and customer acquisition) with respect to marketing decision variables (here, media efforts) (Hanssens et al. 2001).

Two major limitations emerge with this specification. The most important issue revolves around treating potential endogeneity that could bias the coefficients. In dealing with endogeneity, we resort to recommendations using Copula transformation offered by Danaher and Smith (2011) and Park and Gupta (2012). Additionally, we conducted two specification tests to assess autocorrelation and general specification. We were able to obtain stable multiplicative models to produce interpretable elasticities.

The second limitation is related to the nature of multiplicative models and the implications of the estimated elasticities. As a reduced form specification, multiplicative models are prone to the ‘Lucas Critique’ (cf. Heerde et al. 2005). Therefore, a multiplicative-fixed parameter estimation may not be the most appropriate empirical setting. So, we follow Heerde et al. (2005) suggestions in using VAR. VAR models are more suitable for capturing dynamic effects in tactical day-to-day marketing operations (e.g. digital media context) as the ones we proposed in our digital echoverse model.

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Vieira, V.A., de Almeida, M.I.S., Agnihotri, R. et al. In pursuit of an effective B2B digital marketing strategy in an emerging market. J. of the Acad. Mark. Sci. 47, 1085–1108 (2019). https://doi.org/10.1007/s11747-019-00687-1

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Keywords

  • Digital echoverse
  • Digital B2B
  • Digital media elasticities
  • Emerging markets
  • Vector autoregression
  • Inbound marketing
  • Paid media
  • Owned media
  • Earned social media
  • Sales
  • Customer acquisition