Measuring Campaign Effectiveness
The importance of proper coordination between the sales and marketing functions of any organization is a matter whose importance cannot be overemphasized. Although both functions are geared towards maximizing sales and profits, improper coordination often leads to wastage of resources as the sales agents chase leads of low quality, delay the follow-up of leads or dedicate insufficient selling effort towards high potential leads generated by the marketing team. The selling units, on the other hand, more often accuse the marketing team of generating low-quality leads. This situation necessitates the need for an Integrated Marketing Communications Framework (Clow & Baak 2004). This framework is built on the understanding of how various communication channels influence one another and is aimed at bridging the gap between sales and marketing so as to utilize better the resources in both departments (Pickton & Broderick 2001). The three-stage model accounts for how marketing decisions such as those on timing, budgets, and media mix impact on the effectiveness of subsequent selling activities concerning leads generation, securing of appointments with clients and sales closure.
The findings indicate strong and complex relationships among marketing efforts, delays in subsequent communications and the stress that this places on sales. The authors provide three hypothetical situations to show the impact of media changes on the retailer’s operations
The three stage effectiveness model and what each part seeks to measure
The parts of the three stage effectiveness model include:
Stage 1: Lead generation- leads are generated through phone calls received by the call center from potential customers interested in the company products. The leads are usually in response to the company's marketing communications via consumer-oriented means such radio and newspaper advertising and exhibitions and also through telephone directories, the internet, referrals and repeat purchases. The particular communication source resulting to the lead is obtained either directly from the customer by the call center representative or by use of a unique extension of the communication system. This stage measures the number of leads generated by a particular communications source and the impact of communications expenditure on the leads generation. The model postulates that often the leads generated by one source are affected by the communications expenditure on another source. Moreover, the effect of communication costs on lead volume varies with seasonality that is as to whether it’s during the high or low season. From the model drawn up at this stage, researchers can tell the effectiveness of the marketing program since an estimation of the parameters will give the weights attached to different explanatory variables which indicate their impact on the sales or profits and the direction of change (Smith, Gopalakrishna & Chatterjee 2006).
Stage 2: Conversion of leads into appointments- a lead received as a call from a customer in response to the marketing initiatives in stage 1 is acted upon by the call center scheduling an in-house sales visit. However, the conversion of a lead into a sales visit is largely influenced by the timeliness of communication. Some factors affect nonconversion such as the unwillingness of the customer to set an in-house sales visit, an unacceptable time delay between the call date and the sales appointment date or the cancelation of a scheduled sales visit by the client. This stage measures the rate of conversion of leads into appointments.
Lags at a particular time are a function of the prevailing backlog and the new leads in the given period which could exceed some steady state level. For instance, the leads generated from referral programs, newspaper advertising, and telephone directories have a higher rate of conversion into appointments as compared to radio, exhibitions, and direct mail leads. Furthermore, during high season, the rate of conversion of a lead into an appointment is low as compared to during the high season (Smith et al., 2006).
Stage 3: Sales closure- Sales closure refers to the finalization of the sales during the sales appointment, the sales person gathers relevant information that would aid him/her in preparing a quote for the customer. After that, the customer places an order which may or may not materialize. The three-stage model divides the sales closure stage based two parts:
The chances of sales closure given that the sales appointment has occurred and
The size of the sales order given the placement of an order
This stage seeks to measure the effect of the time lag between the sales lead and the sales visits on the probability of sales closure. It aims to analyze the conversion of leads into sales closure. Findings from the model indicate that the longer the duration of the initial client contact and the scheduled sales visit, the lower the chances of a sales closure. However, lags that are customer initiated do not adversely affect the probability of closure as compared to lags that are driven by the sales team. Additionally, the effectiveness of the sales agent calling the households and the changes in seasons affect the chances of closure. The potential order size is thus modeled as a function of the likely order size determined by the size ascertained during the initial telephone call, effectiveness of the salesperson, characteristics of the households and the communications source the generated the original lead.
The key decision of the marketing and sales team involves the timing of communications effort through the three stage channels between the initial sales lead and the sales appointment on the conversion of leads into appointments, then on the closure of appointments to orders. In a nutshell, the three-stage model illustrates how constraints in the sales force capacity are likely to frustrate the marketing efforts of a company. This happens when efforts of the marketing team create more leads which increase the time lag before the sales visit, possibly causing attrition in conversion and closure rates. Just like in stage 1 and 2, the weights attached to different explanatory variables in the regression models indicates the percentage or unit by which one percentage change in the explanatory variable impacts on the dependent variable to be measured. This, therefore, illustrates the effectiveness of the marketing program (Smith et al., 2006).
Impact of current developments in data gathering and market research processes on the three-stage model
Some of the recent developments in market research methods include the use Micro surveys and the Big Data Analytics. Similarly, data gathering is undergoing a lot of transformation in response to the advancement in technology (Couper, 2005). Some of the changes in data collection include the use of the internet, computer-aided self-interviewing such as video or audio and the automated telephone interviewing systems. The emerging technologies and changes in data gathering and market research increase the channels of interaction with survey respondents and increase the range of incentives that can be offered (Poynter & Henning, 2014).
The use of Big Data Analytics which analyzes data in real time impacts on the three-stage model by increasing the speed of data analysis and being able to handle large quantities of data cost effectively (Couper, 2005). The developments impact on the three-stage model by showing relationships between variables quickly and thus aiding in decision making. They also enable the model to factor in data from unstructured or semi-structured sources such as social media and mobile communication. For instance, at the lead generation stage, the marketing team can immediately input information on the communication sources or advertising expenditures and the corresponding leads generated so as to determine the effectiveness of the marketing campaigns in real-time. Similarly, the team will obtain immediate information on the effects of time lag and seasonality on the conversion of leads into appointments and will thus decide whether to increase its sales capacity to reduce waiting times depending on the significance of the impact. This also applies to stage 3 of the model.
New methods of data collection enable researchers to reach a wider audience at minimum costs due to increased internet penetration. They are also convenient as the interviews respond at their own speed and eliminate bias among the interviewees. The use online surveys, self-interviewing techniques and the automated telephone interviewing systems significantly save costs that would have been spent in conducting face to face interviews (Pew Research Center for People and the Press 2011). Some of the drawbacks of online surveys is that it effectively eliminates the potential respondents who do not have internet access. It also prejudices against people with less education, lower incomes, people living in rural areas and the elderly. Moreover, when using online surveys, it is difficult to systematically select a sample from a population. Due to the above limitations, interviewees use other modes to randomly sample respondents and then invite them to attend surveys through the internet (Pew Research Center 2011).
Therefore, the new developments in data gathering and market research greatly improve the development of the three stage model by readily availing data in a cost effective manner. Improvement in market research also helps to establish accurate relationships between the variables in the model, thereby improving the accuracy of the three stage model.
Critical evaluation of Real Time Big Data collection vs the use of Orthodox sample-based surveys
Real-time big data platforms are used to integrate real-time sources and manipulate data in real time. It involves the capacity to use available enterprise data and resources when needed. The platforms analyze and report on data imputed in a system a few seconds before the actual use enabling it to be used to make effective business decisions quickly. Real Time Big Data is applied in updating corporate dashboards to reflect business changes and to field ad hoc questions against large data sets. The management of real-time big data sources is done using specialized technology (Babcock, 2015). This is significantly impacting on data collection since the technology quickly accumulates data that is used in real time. The platforms help to monitor social data, speed up trades, and personalize web experiences in real time. Examples include the NoSQL and Hadoop. These platforms are used to analyze massive amounts of data both quickly and cost effectively and can be applied to unstructured and semi-structured data obtained from mobile communication and the social media (Babcock, 2015). This technology improves sales, raises profits and lowers marketing costs boosting the competitive edge of firms.
Orthodox sample-based surveys involve the selection of sample members of a population, from whom the required data is collected through questionnaires, phone or interview surveys. The data is then classified, analyzed and the findings of which are reviewed on a later date. The use of sample-based surveys is a sharp departure from Real Time Big Data collection in which data is analyzed in real-time using specialized technology. Data collected using sample based surveys is often organized tables and categories to ease the analysis, the data is then analyzed and reviewed thereafter. Depending on the size of data collected, the whole process could take significant amounts of time for the analysis to be concluded and be inferences drawn (Babcock, 2015).
Statistical techniques used in econometric measurement of marketing effectiveness and how these are used in the parts of the three stage model and with Big Data Real Time measurement
One of the main challenges facing online advertising is how to measure and maximize the effectiveness of expenditures on marketing. Expenditure on marketing communication is increasingly being scrutinized to guarantee value. Hence, there is a need to continually measure the results of marketing communications. One of the most important measurement tools that are widely used is econometrics. Econometrics involves the application of statistical methods to analyze economic phenomena. It lays out the relationship between dependent and independent variables and in so doing is used to evaluate the impact of marketing communication spending on sales and profits (Cook & Holmes 2015).
The regression analysis is a statistical technique commonly used in the measurement of marketing effectiveness. This regression model establishes the relationship between the sales or profits and the marketing communication activities such as awareness and image distribution. To enhance reliability, the econometric analysis uses a large data set to draw inferences. A typical regression model is composed of the dependent variables independent variables, parameters to be estimated and the error term. A model illustrates how sales relate to other factors by assigning weights and signs to the various terms of the equation. The weights are expressed as elasticity, and they indicate the change in sales due to a percentage change in the explanatory variables whereas the signs show the direction of change. The signs indicate whether the variables exhibit a positive or negative correlation (Farahat & Shanahan, 2013).
In the parts of the three stage model, various regression models are applied namely:
Stage 1: In the leads generation stage, a regression model is used to show how the volume of leads generated is dependent on exhibition, communications source or communication expenditure
Stage 2: Conversion of leads into appointments, a regression model is used to model the number of sales appointments from the leads against the median time lags between the leads generated in week t and the resulting sales appointments, seasonality indicators. The model also has conversion parameters and an error term
In stage 3, the sales closure is also modeled to illustrate the probability of sales closure at the household level as influenced by seasonality, the salesperson’s effectiveness and the actions of the household.
Therefore statistical techniques are widely used in the three stage model of measuring marketing effectiveness
The Real Time Big Data model also utilizes statistical techniques to establish relationships between variables. This model has in built statistical software that enables it to run an analysis on the inputed data and give results in real-time. The main advantage of the Real Time Big Data model is that it is able to speedily analyze massive amounts of data in a cost effective manner. It can also be used to analyze unstructured and semi-structured data usually obtained from mobile communication and the social media (Babcock, 2015). Thus statistical software imputed in the technology helps to measure the effectiveness of marketing campaigns and thus allows for the prudent allocation of time and resources to maximize sales and profits while lowering the marketing costs.
A critical review of a 2014 IPA Effectiveness Award Paper, outlining recommendations on how I would have improved the measurement of the marketing campaign
IPA Effectiveness Awards are aimed at demonstrating that marketing communications do work and that they produce measurable results with financial value. Additionally, the awards aim to boost the standards of evaluation in the marketing industry. My 2014 IPA paper of choice is the Twix: A tale of two bars- how story telling helped turn Twix into a truly global brand, the paper is authored by Crystal Rix and Lucy Howard. It illustrates how Twix used effective marketing to grow its sales volume and improve local and global market confidence (Rix & Howard, 2014).
The paper begins with an elaboration of the struggles that Twix has had in entrenching itself in the market in the past and the product’s challenge of creating a brand that would appeal to people emotionally. Twix is a chocolate bar consisting of a mix of cookie, chocolate, and caramel; it is a product of Mars Incorporated. In the previous years, the product's marketing campaigns had emphasized on the composition of the Twix and its format of ‘two-ness' as an important selling point. However, this approach yielded unsatisfactory results and failed to outdo Kit Kat, Twix's chief competitor. At the pre-marketing phase, Twix was ranked 12th in the global confections category behind major players such as Snickers, M&M’s, Kit Kat, and Milka. Twix was equally dwarfed in the US market. In July 2012, the company launched a marketing campaign aimed at bringing meaning to the Twix brand to steer Mars business globally (Rix & Howard, 2014).
The Twix marketing campaign involved playing an emotional and entertaining story that would appeal to markets universally but one that still resonated with the Twix brand. The campaign involved engaging the consumer in a game involving the choice between the right Twix and the left Twix although in real sense both are identical and are packaged together. The story behind is that the two bars are produced by rival companies. In this way, marketing team got the consumers to focus on the composition of each bar and the duality of the Twix (Rix & Howard, 2014).
The paper illustrates the impact of the campaign in boosting the global market confidence in the product through the use of a post-campaign survey table that collected data from regional managers from Ukraine. The table serves to illustrate the improvement in brand confidence as explained by the documented increases in product communications in the markets and investor confidence.
I would have measured the effectiveness of the marketing campaign by showing that the increase in sales volume correlates with marketing campaigns and the extent to which the marketing campaigns accounted for the change in sales volume. I would also delink the rise in sales volume from other factors that could have influenced it such as increases in distribution, the price or reduced competitive activities. Moreover, I would measure the effectiveness of the campaign by quantifying the financial value rather than using sales volumes and measure effectiveness of the campaign based on the increase in market share. As part of my analysis, I would collect data and use SPSS software to run a regression model on the effect of the various components of the marketing campaign on the profits and the effects on the improvement in the product's market appeal.
Bibliography
Smith, TM, Gopalakrishna, S & Chatterjee, R 2006, 'A three-stage model of integrated marketing communications at the marketing-sales interface' Journal of Marketing Research, vol 43, no. 4, pp. 564-579., 10.1509/jmkr.43.4.564
Babcock, C. (2015). Big Data Moves Toward Real-Time Analysis - InformationWeek. [online] InformationWeek. Available at: http://www.informationweek.com/big-data/software-platforms/big-data-moves-toward-real-time-analysis/a/d-id/1320952 [Accessed 15 Mar. 2016].
Poynter, R. and Henning, J. (2014). Adoption of New Research Methods. [online] GreenBook. Available at: http://www.greenbookblog.org/2014/09/29/the-top-20-emerging-methods-in-market-research-a-grit-sneak-peek/ [Accessed 16 Mar. 2016].
Rix, C. and Howard, L. (2014). Twix: A tale of two bars - How story-telling helped turn Twix into a truly global brand. 1st ed. Institute of Practitioners in Advertising.
Couper, M. (2005). Technology Trends in Survey Data Collection. Social Science Computer Review, 23(4), pp.486-501.
Farahat, A. and Shanahan, J. (2013). Econometric Analysis and Digital Marketing: How to Measure the Effectiveness | WWW 2013 – Rio de Janeiro, Brazil. [online] WWW2013. Available at: http://www2013.org/program/econometric-analysis-and-digital-marketing-how-to-measure-the-effectiveness/ [Accessed 16 Mar. 2016].
Cook, L. and Holmes, M. (2015). Econometrics Explained. 1st ed. [PDF] 44 Belgrave Square London: Institute of Practitioners in Advertising. Available at: http://www.ipaeffectivenessawards.co.uk/write/Documents/Econometrics.pdf [Accessed 16 Mar. 2016].
Pickton, D. and Broderick, A. (2001). Integrated marketing communications. Harlow: Financial Times Prentice Hall.
Clow, K. and Baack, D. (2004). Integrated advertising, promotion & marketing communications. Upper Saddle River, N.J.: Pearson Prentice Hall.
Pew Research Center for the People and the Press. (2011). Internet Surveys. [online] Available at: http://www.people-press.org/methodology/collecting-survey-data/internet-surveys/ [Accessed 16 Mar. 2016].
