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Marketing strategies powered by Artificial Intelligence and Machine Learning [with examples]

How do you apply Artificial Intelligence and/or Machine Learning to a marketing strategy? With what type of information or action point can a good AI or ML tool help you with?

Everyone keeps talking about Artificial Intelligence (AI) and Machine Learning (ML), and if you would ask five or ten people what is AI or ML you would get different definitions from them. And this is not necessarily bad, as this might be the case for marketing as well.

But how do you apply Artificial Intelligence and/or Machine Learning to a marketing strategy?

As you may know by now, I define marketing as the process and effort of aligning the business with the changing needs of your customers. This all goes to understanding pain points and solving the customers’ problems. And when you need to scale the strategy and apply it, AI may help a lot and optimize the efforts.

💥Marketing AI Example #1

Say you have a SaaS and your outreach efforts in the past year were 3x times higher (Linkedin outreach messages, lead magnet opt-ins, messenger bots content and triggers, SMS sequences, e-mail sequences, new website components, and blog posts) and your budgets for this outreach strategy increased with 300% (or $100k?) — But you still have a rather small bump in the growth curve, instead of a spike or a growing trend in terms of new customers.

Let’s assume you can apply AI technology to your process, how valuable would it be for the company to intelligently analyze automate all the use cases you have in the strategy?
Extremely valuable! Let’s see some real use-cases!

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Photo by Franck V. on Unsplash

🤖 What can a good AI or ML tool help you with?

  • Analyze your current SaaS funnel
  • Check where you have a customer drop in the onboarding process
    analyze all your online content for gaps and opportunities
  • Identify the right trends, topics and keywords to optimize your online content.
  • Showcase the top-performing blog posts, bot messages, action triggers, or any other step within your (outreach) strategy
  • Build new customer journeys and buyer personas based on the data you have in terms of pain points & needs, intents, user behavior within your SaaS and website and based on the goals
  • Detect your SaaS churn based on the pricing model or the pricing tier
  • Identify the right price tier for the right audience and suggest promo campaigns
  • Create a Churner Profile, churner journey, give you a clear overview of their behavior and provide suggestions to improve the journey (or comparisons with the most successful user journeys)
  • provide recommendations in terms of features or content to your customers based on their behaviors and interest
  • Provide data-driven content suggestions (or even create it!)
  • Measure return on investment (ROI) across all your outreach channels and action points and customize the targeted audience based on behavior and lookalike audiences.
  • Identify SEO opportunities and give you optimization suggestions
  • Create real-time marketing campaigns based on trends or highly-targeted content
  • A/B testing your bot messages, email sequences, call to actions or landing pages
  • Offer individualized content across your outreach channels (and even moderate comments across social channels)
  • forecast your content performance and insights before the deploy and provide suggestions to improve the results and achieve your goals
  • create a personalized SaaS onboarding and in-app experience for your customers to increase engagement, loyalty and enhance upsells
  • map your customer journey stages based on their experience within the app, conversations within the chat channels and e-mails data.
  • analyze and provide suggestions in terms of content grammar, tone of voice, audience, formality, and industry field.
  • offer you a scoring system for your leads to identify the conversion rate probability
  • offer a scoring system for your churning customers
  • provide fancy dynamic analytics and data charts and to easily visualize all the above-mentioned performance suggestions and insights

Normally, you'd do this together with your team and it takes a lot of time to go through everything, but using a good AI or ML tools can save you a lot of time and money, as you can tweak your strategies way faster.

Think about Netflix — they saved $1B by using a machine learning algorithm that provides better recommendations and people stopped canceling their subscriptions.

Now, if you do not have the Netflix budget (which I can fully understand), you can always try to use some tools like the AI Score for Marketers from the Marketing Institute to get customized recommendations for AI-powered vendors.
Or you can just use a mix of CRMs, chatbots for conversational marketing (intercom, drift, etc), Yext for reviews, phrasee & rasa dot io for personalized subject lines and content across mails and newsletters, and maybe persado for social media.

Let’s use one of the suggestions given above and apply it again in our SaaS outreach strategy!

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Photo by Hal Gatewood on Unsplash

💥Marketing AI Example #2

From a marketer perspective, it’s easier to think about all this technical thing by looking at your specific challenge. In this case, say my customers churn (or drop) when they need to make a purchase and see the pricing tiers of my SaaS example. Right?
As a marketer, I define a set of rules and content for each tier and if the user goes for one of them, the experience will be different — e.g., if my customer is from the US and picks the mid-tier (say we have 3 tiers), then we should send a sequence of 5 emails with the goal to make the user interested to upgrade to the highest tier. This set of actions is a simple algorithm in terms of Machine Learning.

However, if I want to scale my SaaS and promote it across Linkedin, Facebook, email marketing and some paid ads across Europe as well, then I need localized email sequences, different approaches (maybe only 3 mails for people in Germany and 10 for the ones in Spain?).
And here’s where historical data and personalization steps in!

Machine Learning can help you automate this really fast and grow your SaaS in no time! And an AI will learn how this algorithm performs, will get smarter and will build its own algorithms to optimize and grow the results for you!

Pretty cool, isn’t it?

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Photo by Mark Fletcher-Brown on Unsplash

How do you know if you can apply AI or ML to your Marketing strategy?

I know these are the two buzzwords that you keep hearing. And maybe you do not even need to implement this within your company! But if you wonder if it makes sense to pour any effort into all this Marketing AI and start a pilot project using new tech, here’s how to run a short assessment!

  1. List all your efforts on a paper. or in a doc, whatever makes you happy :)
  2. Now ask yourself the following:
    Does it use any sort of data? Should it? What would you like to know about this action point?
    Is it repetitive?
    Do I have any sort of predictions or forecasting for it? would it help to have?
    What would help you enhance or boost this effort — say regular content or knowing what’s the current gap in terms of content in your industry?
    Can it be standardized? can you use templates or action-triggers for it?
    what type of reports do you have? what type of reports you have to create? how often? why? is it helping? how do you ensure you implement the action points from the reports’ insights?
    Do you use the trends to do any of your listed actions?

If you go through all your list and ask yourself the above-mentioned things and you see there is a lot that can be done automatically and it makes sense to pour tools into it — go for it! If not, then enjoy doing these. Data is fun ❤ especially if you use it for taking smart decisions for the company’s growth and cost reduction :)

What are the 5Ps of Marketing AI

If you decided to apply some AI to your Marketing strategies, you are already aware of all the Ps we love in this industry. I will not go through the classic Ps, but here are the 5Ps of AI (especially for Content and Email Marketing):

  1. Planning
  2. Production
  3. Personalization
  4. Promotion
  5. Performance

Who uses Marketing AI or ML?

Facebook, Google, Instagram for their ads, Netflix, Adobe, Spotify and pretty much any big company you use on a daily basis and you love :)

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Photo by Andy Kelly on Unsplash

Will AI steal my job?

No idea :)
Most jobs that exist today, did not exist a few years ago. We keep evolving, so even if most of your activity will be done by an intelligent too, you will still have a lot more time and opportunity to use your creativity! Not to mention that you can train the tools to do whatever you want to know — so, it's your intelligence that makes them work for you :)

Thanks for reading me! Do clap if you liked it, share it with your community or team and let me know if you have any suggestions or feedback!

Working with tech products that always have a cause and solve a problem | Data-Driven Marketer • Strategist • Product & Startup Enthusiast • Occasional Speaker

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