A range of variables are used to ascertain whether campaigns are effective. However, the one indicator that was mentioned across the board is sales: “Is it the sales, because that to me is
how efficient the sales force is in converting leads derived from the campaign’s responses:
“it’s trying to shorten the phase to make it easier for the sales force to sell”. Other indicators used in analysis of campaign effectiveness are reach statistics, brand recall during audience testing surveys, frequency of advertising and the value of the marketing budget spent in relation to projected audience reach numbers in the media planning phase: “sales, brand recall and then maybe …the hype created around the messaging of people talking about the product”. Social media engagement was also discussed: “Because interestingly enough, in the ... space, this year alone there’s been a lot more focus on financial services, particularly in terms of social media”. However, the consensus was that this channel is more appropriate for service-related and client engagement purposes than for traditional marketing, especially when attempting to sell a product or service: “And it’s kind of like people tweet when they’ve got something to bitch about. Or complain about service. That’s when they tweet, that’s when they jump on Facebook. So our primary role is to monitor those platforms and make sure who’s calling. To stop what’s a potentially small little issue from getting bigger.”
Sales-related figures such as the number of leads and conversion rates, including sale-to-contact and agent productivity ratios, are also important to be able to manage the fulfilment cycle: “How many calls, how many leads were generated, how many of those leads were valid leads because you say SMS your name to this number.” Internally focussed indicators for cross-sell campaigns to an existing or affinity base of clients, such as customer satisfaction and client engagement statistics, are used to target clusters of clients with certain value propositions more effectively. The tracking of the responses are also an important factor: “everything is perfectly trackable, but the call centre, one the first questions they ask you is ‘what advertising prompted you to phone us today?’” This means that dedicated response channels (such as e-mail addresses or SMS numbers) need to be assigned to a campaign to truly ring-fence its outcome. Some companies have developed in-house metrics to track campaign efficiencies. These metrics are based on product profitability, embedded value and turnover numbers to ensure campaigns are business-case driven and managed effectively. The marketing statistics, in terms of responses, contacts and sales are then expressed as a factor of these profitability indicators to ensure a consist approach: “We’ve got a thing called a p factor, which actually is there to measure the overall success of our marketing spend. And it can be broken down right down into different media channels and into different media owners. So we can calculate what is a p factor for TV and p factor for radio. Within TV, what is our p factor for MNet versus SABC versus eTV. And the p factor is
simply the multiple of the number of months of premium that it costs us to acquire a client. So it will say TV is running at a p factor of 3. And it means it’s taken us three months’ worth of somebody’s premium, on average, to acquire that person. So if our average premiums are R700 a month, and we say we’ve got a p factor of 3, it’s costing us about R2 100 to acquire a client and get him on the books. That’s a sale. So that is simply the ad spend divided by the premium that that ad spend generates. That’s the formula. We also look at a thing called an l factor, or a cost-per-lead, which is simply the advertising spend divided by the number of leads that advertising has been generating. So that gives you an indication as to how many quotes does it generate”.
Brand awareness was also discussed intensely and although the equity within a brand was thought to have an enormous impact on the outcome of a direct-response campaign, awareness statistics in itself was generally dismissed by the participants as an indicator of campaign effectiveness: “The biggest job as a brand is going to have to be to build brand trust.” Client retention numbers were also marked as important to keep in mind when targeting market segments to ensure that the positioning of the message as well as the media of the campaign reach the correct audience.
6.3. SUMMARY
The focus group discussions contributed towards an in-depth understanding and identification of the themes that are essential to build a metrics model for direct-response advertising in the financial services industry. These themes contain all the sub-factors or variables that need to be taken into account when campaigns are planned, executed and measured. The themes identified, in no particular order of importance, were as follows:
• Client acquisition
• Client satisfaction
• Cost
• Creative quality
• Loyalty
• PR
• Profit
• Reach and frequency
• Sales
Table 6.1 indicates the sub-factors or variables linked to these themes.
TABLE 6.1: ESSENTIAL THEMES AND THE SUB-FACTORS OR VARIABLES
These themes were weighted in order of importance for the successful execution of a direct-response campaign through AHP and by a survey containing pair-wise comparisons that was sent to marketing practitioners and strategists in the financial services sector.
The secondary research aims, as discussed in chapter 5, are further underpinned by these themes’ underlying inter-related variables that represent inputs as well as outputs as highlighted in Exhibit 6.1.
EXHIBIT 6.1: ALL IDENTIFIED VARIABLES FOR THE PROPOSED MODEL
CHAPTER 7
MODEL CONSTRUCTION AND VALIDATION
7. INTRODUCTION
The quantitative survey conducted for this study, was targeted at Marketing strategists and practitioners within the financial services industry. A representative sample consisting of 352 respondents, representing all facets of the financial services industry, was invited to participate. These respondents represented all the fields within the marketing fraternity, from brand specialists, to client management and advertising specialists, as well as communication and direct marketing practitioners. Full responses were received from 103 respondents, representing a 29.2% response rate. These responses were used to weight the underlying themes within the model, through the use of Analytic Hierarchical Processing.
7.1. MODEL COMPONENT WEIGHTING