Every marketer and e-commerce manager wants to know how effective their advertising is. But having a holistic overview of the business and an ability to understand the full customer journey has proven to be a challenge for years. A challenge not made easier by the introduction of something like iOS14.5. But there might be an answer to the issue.
Social media analytics tools offered by platforms like Facebook, Instagram, and Twitter are a start in helping you understand the effectiveness of your advertising. But social media analytics tools cannot tell you how effective your ads are beyond the platform on which they run.
A customer data platform (CDP) lets you unify data from multiple sources to better understand what’s working. As well as what’s not across all of your marketing channels.
Context is king. This is true for social media analytics, and it’s also true for data, integration, targeting, and measurement in e-commerce.
The context in which your data is being collected and analyzed can be the difference between success and failure. This is especially true when it comes to integrating your social media activity into a larger marketing strategy that includes paid advertising on social networks as well as other campaigns like email marketing.
When you know what channel each piece of content was originally posted on. (And where it landed after being shared). You can tailor subsequent posts accordingly. Not just by channel but also by time of day and geographic location.
In other words: if you want your audience to see something in their feeds. Make sure they see it when they’re online!
Social media analytics is a subset of digital analytics. They help you measure the effectiveness of your social media marketing campaigns. They also give insights into how customers engage with your brand on social media platforms.
Depending on what you want to achieve, there are many different types of social media analytics that you can use to track your progress:
However, these analytics are typically siloed into this one channel. And it does not give the context to understand your customer better. Siloed data means you might draw conclusions based on a data set that is simply limited in its ability to provide valuable insights. This means you won’t understand the full effectiveness a campaign has on your customers’ journeys.
As you can see, there are a lot of different ways to use your social media analytics. But what if you want to understand the full customer journey? What if you want to break down silos and connect the dots between your social media data. Or maybe some other touchpoints or customer data, customer experience, and satisfaction?
That’s where CDPs come in. A CDP is a central system that allows for seamless integration between various sources of information about customers. It’s also an intuitive tool that lets users quickly analyze their data using visualizations or dashboards. And then use it as a starting point for deeper analysis.
Social media goals are not always the same as your overall business goals, but they’re often related. A CDP can help you ensure that your social media efforts support your larger objectives.
For example, if you set up a CDP around “increased brand awareness,”. It will tell you how well your posts are doing in terms of generating mentions and impressions from fans who aren’t already following the brand.
If this is an important goal for you (maybe because it’s part of a broader strategy). Then updating this metric based on new insights from a CDP would help keep these efforts on track and make them more effective over time.
Social media analytics provide insights into the performance of your social media activities. However, they don’t give you a complete picture. By themselves, they can measure engagement and conversions but not ROI or campaign effectiveness.
With a customer data platform (CDP), you can expand the scope of your analysis beyond what’s possible with social media analytics alone. CDPs enable you to use data from multiple sources. This includes public records and third-party services. So yo can create richer, more accurate profiles of users who engage with brands on social media platforms.
For example, CDPs enable marketers to compile detailed customer profiles that include all of their purchasing histories at brick-and-mortar stores. Or it could be online purchases made via smartphones or other digital devices in e-commerce stores.
A wealth of information like this enables marketers to target ads based on more than just where someone lives; it also allows them to segment audiences according to lifestyle characteristics such as income level, family size, and or other determining metrics that can help you target more precisely.
Lookalikes are one of the most preferred ways to grow your customer base. Especially in recent years, machine learning has become so powerful that data-driven marketing is a must for any modern marketer. Finding more people who are similar to your most valuable customers sounds great, but is it too good to be true?
The way it works is that it takes your best customers and uses an algorithm to find similar people. You, the ad spender, only have to choose what segment to find lookalikes to and how closely they have to match your audience. Here you choose between the numbers 1% to 10%, where 1% is the most closely matched lookalike audience.
A good rule of thumb when dealing with an algorithm is, that the better data you feed the machine the better results you get. Currently, the data being used right now by businesses on Facebook only comes from Facebook itself. However, it is possible to get aggregated data that is more specific.
By using a Customer Data Platform, you collect data from multiple sources to get the most specific customer segments in real-time! This data might be aggregated from your Shopify, google analytics, Facebook, Klaviyo, you name it.
This data is now a lot better. How? By aggregating data you get segments that you would not have had, if you had been using Facebook’s data only.
This is because the data used before maybe didn’t account for metrics like return rate or order frequency. By getting all the most important data from multiple sources it is possible to get the “true” lookalike audiences.
If you are not using a CDP to get the most out of your social media analytics, then you may be missing out on important insights about your customers. You can use these insights to improve your targeting and measurement techniques across channels and devices. This is leading to better results in the long term.
A normal human being would be able to see no connection between the people in the segment. But, the algorithm recognizes similar behavioral tendencies, which makes it possible to find lookalikes, in this case, really good lookalikes.
So using aggregated data and therefore more specific data makes your lookalike audiences a lot more powerful. All this makes it possible to grow your customer base faster, than using siloed data from your social media analytics.
Combining that with machine learning and analytics tools like a Customer Data Platform, you can get much more out of your social media analytics.