Digital Loyalty: Beyond Likes, Re-Tweets & Shares
I,
like many others reading this (I hope!), have faced the challenges of designing
& developing a customer loyalty program. There were times when implementing
loyalty programs were the preserve of the marketing barons and czars & now,
the current marketing landscape has spun the entire ecosystem around its axis.
Now, every marketer has tried, run (and regretted!) some form of the in-season (social
media) loyalty programs (not to mention counting likes on Facebook, RTs on
Twitter). Which brings me to the topic of my current post: In the era of “fluid
fingers”, how can a marketer build loyalty and what can they do to stop jumping
from one in-flavour loyalty program to the next?
Loyalty? Now? You must be crazy?
In
marketing currency, customer loyalty is platinum grade ingots that marketers
would be willing to commit black marketing to acquire. Now, when more than
ever, loyalty is increasingly being interpreted as “likes” “follows”, and “retweets”,
marketers need to step back and assess how many of these metrics are actually adding
business value.
Lessons Learnt: The Hard Way & Otherwise
How Digital Loyalty Helps: Having run campaigns on social
media, I can’t complain about conversions, but traversing the path from
conversions to loyalty is the marketing equivalent of a Mount-Etna-esque walk.
- Engagement First: What I’ve found is that social media is good for initiating dialogue; challenging viewpoints, engaging audience, and then identifying brand advocates. Social media loyalty pages help people in connecting around a shared idea or a brand that they love/hate and creates a sense of participation. But extending their love for the brand on social to extrapolation of their purchase probability, might be, in some cases, extreme. But their positive WOM may be itself equivalent to a quarter worth of PR.
- The Social Influencer: Social media helps marketers to deep dive into the influencer sea, identifying relevant product ambassadors, and their sphere of influence, especially for products around which consensus is needed or is a high risk, high value product. A fantastic illustration of this is the 1-9-90 principle (more at http://slidesha.re/110oOoH). Ones are the “Big Fish”, popular on digital media, the caveat being that everyone covets them, thereby making them harder to “acquire”. For these individuals, it makes sense for the marketer to engage in 1:1 digital dialogues and cultivate relationships with them long-time. Nines are the niche experts, those that wield considerable influence among small focused circles and for them the key marketing consideration is relevance. Nineties are the silent majority, and with them, the key consideration for a marketer is visibility (More on this in the next post).
- Heart-ily yours: Who doesn’t love 10,000+ likes on Facebook? But what does that translate into, and whatever it does, is it valuable to you? If your 10,000+ fans are actually attitudinal loyalists (share of heart), then I would say stick with them like glue, because they are as important as behavioural loyalists (share of wallet) and if you focus on getting the heart first, the mind and the wallet follows (most of the times).
The
point that I am trying to make is that with the host of applications available
on social media for building loyalty, it is an optimization problem for a
marketer, with very little ROI analysis tools available to let us know a quick
A/B test for the effectiveness one loyalty program versus the other. If you are
a marketer with a resource crunch, the per-activity ROI may not justify
maintaining such high-engagement programs. In cases like these, the above
mentioned pointers could help.
How
Digital Loyalty Tricks
Just
the fact that countless customers now have a name, a picture and a community on
social media, marketers tend to get intoxicated just by being able to do
something “cool”.
- Stop Tracking Vanity Metrics: For a budget-constrained marketing program, the worst thing to do would be to invest time in counting recounting likes, followers, fans, retweets, shares. These numbers would (only?) mean that the brand correlates well with the target audience online but “100 shares doesn't necessarily mean 100 sales—and it certainly doesn't measure the potential value of those 100 shares” (http://on.mash.to/16oj80s) Most marketers don’t have the tools to correlate these digital marketing metrics to a potential sales pipeline, and this ends up reflecting poorly on marketers, investing resources in an activity with no scientifically justifiable sales correlation. Likes are good, but that’s what they just are. Good, not good enough.
- The economic value of a “like”: Tetra-trillions of data is created purely through social media (giving birth to that monster, Big Data, more on that in the next post), data which is sub-optimal. But what is the economic value of a like? Before a conversion happens through digital media, you have an assessment of its economic value, a goal X, of value Y. How strongly is loyalty correlated at all to the marketing metrics that we are tracking? The right metrics to track are “uncool” and undigitized, but those are the ones that need to be taken seriously. As pointed out here (http://bit.ly/ZvTcgq) by Kaushik, what matters is tracking down the conversations around an idea/post and that is, ploughing through mountains of data, definitely data intensive and uncool, but much more valuable. The operative here is to “hear out” customers not to “dump in” data.
- Crystal Balling: The ultimate acid test is conversions and repeat business. Rest all is a distraction. Cut the clutter & get to the chase. A lot of (not all, please) the present loyalty tools are generating volumes of data, reports, analytics, all of which are contributing to gigabytes of trash (I have come across some randomly stupid metrics, which were not valued by sales at all, and were not at all correlated to conversions & repeats). All those metrics were leading to crystal balling, never ending “what-if scenarios” and driving the focus away from the customer.
Not
all (even none) of what is written here may apply to you, and if doesn’t, paste
the link to your post here!
Before anyone trumps me to this..there would be issues around scaleability that would arise around the line of thought mentioned above...but using scaleable models didnt help me!
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