INBOX INSIGHTS, February 9, 2023: Technical Continuity Planning, Twitter Scraping

INBOX INSIGHTS: Technical Continuity Planning, Twitter Scraping (2/8) :: View in browser

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Technical Continuity Planning

Last week I talked about business continuity, and what happens when people leave. But what happens when the software you rely on to run your business makes a major change without warning? This is where you need technical continuity.

A good example of this is when Google gave us ample warning about moving from Universal Analytics to Google Analytics 4. They rolled out the new system in late 2020 and then announced the sunset of UA roughly 18 months before it would happen – this coming July.

By the way, if you haven’t moved to Google Analytics, give us a shout. We can help!

But what happens when you don’t get 18+ months notice that you have to start using a new platform, you have to migrate your data, you have to create backups and modify your processes?

Twitter just did this to us. To all of us. Without warning. Since the major change in leadership, functionality has been changing just about every day. Companies and users that rely on that system for their business are scrambling to plan for the unknown. Most recently, Twitter announced that they will shut off free data export access via their API. You can read more about that in the Data Diaries below.

So, back to the question at hand, do you have a technical continuity plan? If you have a business continuity plan, you likely have plans for the departure of key resources and IT systems at the core of your business. But what about the lower profile systems, like your social listening and SEO tools? These won’t be a high priority to your executive team, but to you they are completely essential.

This is where your technical continuity plan comes into play. Much like we talked about last week with business continuity planning, your plan doesn’t have to be overly complex. We’re going to use the 5Ps again as the structure for a simple technical continuity plan. We can use social listening as the example.

Let’s start by understanding what you need the software for:

Purpose: To understand what is being said on social media about our brand and other keywords that we care about. This is a service we offer to our clients.

People: The social media manager that pulls the data and the clients that rely on the output.

Process: We pull daily reports from the system based on our search criteria and make decisions with the data. We package up this data for our clients daily.

Platform: (for this example) Sprout Social

Performance: The data from Sprout Social alerts us to conversations happening online that our clients need to take part in. When we ship insights to our clients, they use the data to make social strategy decisions.

Now that we have a baseline, let’s imagine that Sprout Social decides to change course and stop offering social listening (this is not true). They only want to handle social scheduling (again, not true). You’ve already noted that this is one of the services that you offer, so not having this functionality will have negative financial implications. You have a good understanding of what this software does for you and you can start to prepare for the risk of not being able to use this software.

While you don’t have to have subscriptions to other tools, it’s not a bad idea to have a short list of tools that can do similar things to the one you’re currently using. When Google made their announcement about Google Analytics 4, many started to look into tools like Matomo and Adobe Analytics. Switching software platforms can be a pain if you’re caught off guard, especially when you have a lot of data involved. Having a technical continuity plan can take the (some of) the stress off your shoulders when a platform you rely on makes a major change.

Do you have a technical continuity plan?

Reply to this email or come tell me about it in our Free Slack Group, Analytics for Marketers.

– Katie Robbert, CEO

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Data Diaries: Interesting Data We Found

In this week’s Data Diaries, let’s talk about Twitter data. A week ago, Twitter’s management made the sudden, very surprising announcement that access to even the basic API would now carry a $100/month fee, effective as of February 9 (the announcement was made on February 2, which is terrible change management). While this makes good sense for some commercial users of Twitter data, it’s substantially problematic for many more users. For example:

  • Developers who want to build applications on the Twitter platform can now no longer even test their apps without paying
  • Non-profits and other non-commercial organizations who use Twitter data will need to pay for it, even with no profit motive for it
  • Fun applications, such as webcams that transmit photos of someone’s cat or weather bots or other barely-commercial uses will now also need to pay

For those of us in marketing analytics, we have become accustomed to using Twitter data as the backbone of influencer marketing. Many applications vacuum up large amounts of Twitter data to use for building influence graphs; Trust Insights has published dozens of these graphs over the years for events we’re not attending, just as a way to stay in touch with and highlight some of the many communities we like.

So what are the alternatives, if you don’t want to pay or you’re unable to pay for access to the API? Depending on your use cases, affordable or free open-source alternatives may fit the bill. For example, the snscrape Python application is capable of extracting data from Twitter’s web interface. And for those concerned about legalities, while you should always consult with your legal counsel in the jurisdictions in which you operate, for USA-based companies, the Ninth Circuit of Appeals court reaffirmed that web scraping of public information is legal.

What does a utility like this do? Fundamentally, it reads through the Twitter web interface and compiles the data for your search term into some data storage format which you can then analyze. For example, we could monitor the hashtag #GoogleAnalytics and then look at what’s happening on that hashtag over a long period of time. And because it doesn’t use the API, it’s not constrained to the API limits:

R dataframe of Twitter data

So what? The key takeaway here is that we constantly need to be monitoring and looking for solutions to deal with unexpected technical issues. Sometimes they’re issues of our own making, but in the increasingly SaaS-based world of marketing technology, it’s issues foisted upon us by technology we don’t control. Cloud computing has rightfully surged over the past two decades to become the dominant form of computing, but for anyone whose business relies on data, it’s always a good idea to have a backup plan, an ace in the hole that you control.

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