You need digital analytics because, without appropriate metrics, your social media strategy flounders.
Here’s the reality of digital analytics today:
- Brands don’t measure
- Brands don’t measure the right things
- Brands only measure the bottom of the funnel actions
- Brands don’t measure on a consistent basis
- Brands give up on social media too fast
Digital analytics optimization
Brands don’t measure
Any number of brands complain they aren’t achieving success with social media marketing. When I ask what their analytics look like, they have NO clue.
Metrics are a consistent problem for marketers. Either they don’t measure the effects of marketing strategies or the things they measure don’t impact marketing goals. Let’s address each problem separately.
Why don’t brands measure the impact of their marketing strategies, whether digital or traditional?
Part of it is historic. Marketing, except for marketing research, doesn’t have a tradition of analytics.
Maybe it’s a function of marketing’s break from economics over 75 years ago.
Maybe it’s a function of marketing’s reliance on psychology to understand consumer behavior.
Maybe it’s just a function of training.
Whatever the reason, marketing suffers for its lack of hard-core metrics and focus on analyzing ROI. C-suite decision-makers want hard numbers to justify expenses and, without those metrics, marketers can’t argue effectively for their strategies.
Moreover, without effective marketing metrics, marketers can’t tell what works from what doesn’t. Their own strategies might not be the right ones or might not optimize market performance.
Anyone who’s been around for a while knows the squishy metrics used by traditional marketing to support strategy — increased awareness, improved sentiment. The assumption was that these metrics translated into ROI, but the connection was always tenuous — and may be absent altogether.
The exception is direct marketing — which is where I got my early training. Because its materials were tangible, we KNEW how many folks bought based on a specific campaign and we could do effective A/B testing to determine which offer outperformed others.
And, we need that level of analytics in today’s marketing. Digital analytics should optimize market returns.
Brands don’t measure the right things
If I had a nickel for every client who focuses on vanity metrics as their only digital analytics, I could retire.
Sure, vanity metrics such as #Fans, #Followers, #Likes, #Shares have meaning, but you really need more detailed metrics tied to smart goals. Even vanity metrics are less valuable without some granularity to understand what actions impacted your vanity metrics.
The first step is establishing goals for your digital marketing — from across the funnel (see below). Next, determine KPI (key performance indicators) related to your goals. Here’s a list I cultivated as a starting point in assessing your digital analytics.
Next, determine which digital analytics tools meet your needs in terms of both delivering accurate KPIs and your budget. I have a list of digital analytics tools that’s pretty comprehensive because folks keep adding to my list. Feel free to add your own favorite digital analytics tools or vote up the ones that are there so the list becomes more valuable over time.
I’m a big fan of dashboards and your preferred digital analytics tools might not bring everything together, especially if you’re using several different tools. I like IBM Cognos for bringing metrics into 1 place and helping visualize trends (which are much more important than isolated point metrics).
Brands only measure the bottom of the funnel behaviors
Sure, the bottom of the funnel is where the cash registers ring, but ignoring top of the funnel means you’re not building conversion. To accurately move folks through the conversion funnel, you need to optimize performance in getting them into the funnel and reduce the number who leak out of the funnel.
You need metrics aimed at each element in the funnel — new visitors, sentiment, etc.
With Google Analytics you can even map your content to the appropriate stage in the conversion funnel, then assess performance using Google’s funnel option. It’s a relatively simple process of identifying various paths leading visitors through your website to conversion — whether that be subscribing, downloading your white paper, accessing store locations, or completing a sale. You can get detailed instructions on setting up a funnel in Google Analytics here.
Brands don’t measure on a consistent basis
I look at my digital analytics every day and generate a more granular report every week for myself and my clients. That works well when you have a couple of thousand visitors a day. Once you get thousands of visitors an hour, you need real-time analytics to monitor performance and make changes on the fly.
Remember, there’s a cost/ benefit tradeoff when it comes to any analytics, including digital analytics. You only measure as often as necessary to optimize market performance. Measuring more frequently doesn’t improve performance relative to the cost involved while measuring less frequently means you’re not optimizing returns.
Brands give up on digital marketing too fast
Marketers seem to expect massive ROI from digital marketing immediately. But, marketing doesn’t work like that.
As a new brand or one that doesn’t have much of a digital presence, you’ll need to focus on building platforms and beginning to drive prospects down the conversion funnel. That takes time and a lot of effort.
Digital marketing works like this bucket. You pour effort into it and only when your efforts rise to the top of the bucket will ROI begin to flow out the top.
Obviously, the more efficient you are in filling the bucket, the quicker you start seeing market returns. That’s where digital analytics comes in.
Digital analytics monitor how your target market responds to your marketing efforts and guides you toward optimizing efficiency. Once you see what resonates, you simply do more of it. As your bucket fills, you’ll see market returns.
The bucket analogy implies we need to focus on metrics reflecting how content resonates with our target market by generating engagement and building a strong social network.
The digital analytics compass
The digital analytics compass or social media analytics compass comes to us from Razor Social (BTW, check out their other great content).
Let’s start at the top and work our way around the compass clockwise:
**Remember to measure these elements periodically. Once is never enough because digital marketing changes over time and what works today might not work tomorrow.
Audience
Sure, the more you pour in the funnel, the more convert so audience size matters. Audience composition matters even more because it doesn’t help to reach folks who aren’t in your target audience (persona). Google Analytics helps understand who visits your website by including Demographics, Interests, and Cohort Analytics. You first need to turn on these features as they’re not part of the default analytics provided. It’s also a good idea to link your Google Analytics to your WebMaster tools to get a clear picture of audiences coming from both paid and unpaid traffic. You can learn more about turning on these functions here.
Twitter offers a relatively general breakdown of your Twitter audience while Social Razor recommends setting up a Facebook ad targeting your followers. Without even running the ad, you get an estimate of how many followers fall into each group you target.
A critical element of your audience is identifying influencers and advocates. These actors have a huge impact on your market performance. By identifying these actors, you can proactively reach out to increase their actions that support your market performance.
Content Analysis
Content creation/ curation is expensive and time-consuming so you want to ensure you get value from it. Measure:
- What content drives clicks to your website?
- What types of content or pieces of content generate the most engagement?
- What content drives other actions such as subscriptions or downloads?
- Are there patterns among pieces of content that perform well? Poorly?
- Are you responding appropriately to your community? If not, how can you improve this?
- How does content sharing help build your community?
Competitive analysis
Identify competitors and understand what they’re doing.
There are 2 parts to understanding how competitors approach digital analytics.
First, see what works for them and what doesn’t. This saves you from making many of the same mistakes they do.
Next, identify elements missing from their digital strategy — these represent a huge opportunity for your brand.
Finally, don’t copy what they’re doing. Find your own unique path to engaging with the same digital audience or segmenting the audience to customize your approach for each segment. In a head-to-head competition, there are winners and losers. When using a unique strategy, each can come out a winner by building on their strengths.
The digital analytics and digital marketing areas are very crowded and it’s hard to stand out in that crowd. Hence, I chose a different pathway building on my strength as a marketing professor. I have a deep knowledge of marketing concepts that is unmatched by my competition. So, I build on that strength by using marketing concepts to ground my advice.
And, it’s working.
Sentiment analysis
Often, marketers define sentiment analysis pretty broadly as positive or negative. That’s unfortunate because sentiment analysis is much more nuanced including all attitudes related to your brand. In addition, you should look at:
- Suitability of your brand — this is probably the single biggest factor in determining buying intentions
- The value offered by your brand
- Responsiveness to customer queries/ complaints
- Recommendations
- Usage rates and occasions — you want customers to buy more frequently
- Loyalty
In addition, social media offers opportunities to identify unmet needs which suggest new product offerings.
A couple of caveats seem prudent at this point.
First, analyzing social media has dangers; the most serious being that vocal users often aren’t representative of the group and, in fact, are often statistically different from less vocal users.
Second, unless you’re a relatively small brand, you’ll find you have too much data to effectively analyze without a text analytics tool. Unfortunately, these tools suffer a myriad of problems ranging from long training requirements to poor performance. They do especially poorly with slang and another language you’ll find common in social media.
My recommendation is to use the tools (my particular favorite is HyperResearch because it allows hypothesis testing), then do a manual analysis on a random subset of texts.
Final thoughts on digital analytics
I hope you find this article helpful. If you have specific questions or have a topic you’d like me to cover, please ask in the comments below.
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