Social Networking: The Corporate Value Proposition
LEVEL 3 – Qualitative measures
Some marketers in this ‘advanced’ category optimize their operational practices and brand- execution value proposition the same way that they work to optimize their ad spend. This has led to use of qualitative measures to support operational questions like: What are our customers’ individual needs? How good are our insights into the way our customers regard and connect with our brand? How and when can we best engage our customers and enlist them as collaborators? How innovative, differentiated, and resilient will our brand continue to be in these commoditized and competitive times? Our 2009 article gave some examples of social media qualitative metrics that bear repeating: customer share of wallet, reasons for changes in composition of customer lifetime value and satisfaction, channel effectiveness related to customer needs, and effect of time to market, pricing power, and brand equity. The aim is to get dynamic insights into brand engagement, audience captivation, level of interest, and content curation – why people buy, what triggers a stretch-purchase, who the key influencers are, and what strengthens relationships? Until these questions can be answered adequately, these qualitative measures will inform a C-suite member’s decision but not direct it.
LEVEL 4 – Modeling
There is an emerging fourth level in the hierarchy, modeling planning-related data. This is so far a relatively underdeveloped (and under-automated) aspect of marketing practice. As discussed in the rest of this article, it involves creating social media analytical models that synthesize the complexities of both volume and qualitative data – with value projections, iterative ‘what if’ calculations, decision criteria, and prioritization of activities. The challenge for modellers is to eliminate the bias inherent in the mathematics underlying the business-as-usual mix optimization models that have been in use for over 30 years now. A message to econometricians: it is no longer business as usual so stop running those forecasts. More than any other decision makers, marketing planners tend to get this.
Empirical results from brand lifecycle activities example: Mark Daprato, VP, Marketing at Swiss Chalet, measures “the social media cost of acquiring a fan, the incremental benefit of unpaid content compared with paid clicks, and soft benefits like fan responses to an on-line customer complaint posting” that together provide social media value added. He adds that brand lifecycle only delivers a return when you reach the affinity stage with customers.
Level 4 (modeling) in our view is the most robust — and is essentially the platform on which the rest of this article is based.
Actual measurement practices in supporting specific brand planning can often be somewhat experimental. Examples related mainly to the first three levels are illustrated in the boxes containing comments from three of the leading marketers we spoke to. Their comments reinforce the understanding that a combination of quantitative and qualitative marketing measures helps the marketer improve interaction tone, quality, and benefit to the customer – not just in social media but across the full spectrum of the business.
2. Sales lift vs. customer relationship value lift
Modelling is not just for use in internal marketing. It can also to be used to answer questions posed by the other members of the C-Suite about those value-specific marketing activities that deliver value for the organization. Marketers should avoid overwhelming their colleagues with too much data, but they do need to provide a convincing justification for social media investments. They also need to distinguish the implications of sales lift from relationship lift.
Opportunity cost example: Frank Trivieri, GM Canada’s General Director, Marketing, says that social media is not just a mechanism that gets the message out but one that “enables us to listen closely to the customers.” He is mindful of the opportunity cost from not doing this – “If we don’t connect effectively in social media channels, we will miss out on key conversations and opportunities to engage people who may never have had GM on their radar before.” Trivieri uses a commercial measurement tool to track net positive/negative comments, to augment traditional audience activity metrics like increases in numbers of pages viewed, brand scores, etc. and has established a cross-functional social media council at GM Canada to ensure that the company remains relevant and accessible.
Marketing analytics historically has tended to be more about product than customer, i.e. incremental units sold or, less helpfully, incremental ‘conversations’. Some in the leader category of brands claim to be able to map the connection from creating demand awareness to a conversion. But in social media it is hard to find anyone able to seamlessly replicate the process that got the consumer there the first time. Hard results from specific promotional activity are often easier to measure than soft benefits from improved relationships. We would like to see this reversed.
A typical product-planning model is based on the direct marketing deal – for example a coupon or a price cut, maybe backed by a print or TV advertising campaign. It is not surprising that many of these models originated in the advertising industry.
Several social marketers we spoke to have found it quite difficult to adapt traditional advertising interaction models to on-line interactions, even when deal-based. Perhaps, insufficient on-line history has yet been accumulated to refine their model assumptions.
The promotional approach to social media appears to have staying power. Our research indicates that companies posting deals on social media generally express satisfaction with results, claiming the direct marketing approach is generating incremental sales and customer receptiveness.