Maximizing Your E-commerce Revenue, Part 2: Make your customers feel like they belong.

So, this is part two. (Duh.)

If you haven’t already read part one, read it here (insert link for Part 1 here) and then come back, so that you’re not missing out on anything.

If you have, it’s all good.

Anyway, so today, we’ll be continuing with…

Personalization.

And no, it’s not as simple and easy as greeting them by their name on your home page after they log in and suggesting products based on their previous activity and purchases.

Sure, that IS one of the things you could do but…

Why start there?

There is so much potential here when it comes to the things you can do.

In-session retargeting, personalized emails to get them to continue shopping, adding exit offers as well to make the most of every moment they spend on your website…

There’s just so much. So, let’s get to it.

"Drew. Why? Why? Why do ALL this? WHY?"

Well, besides the fact that it's beneficial for your business and increases customer loyalty, leads to better sales conversions, and helps improve brand engagement...

There’s the matter of standing out in the crowd.

Giving something different to everyone who visits your com website.

Something they don’t always get when they set out to make a purchase.

Differentiating your brand from all the other e-commerce brands out there.

But above all…

It’s about delivering a truly relevant and personalized experience.

One without the clutter.

One where you suggest the things they want.

One where they feel guided through all the extra things toward the section they'll immediately like.

One where they don't feel like they're just another sale toward a sales target.

And all of this…

Dynamic landing pages change depending on where someone is viewing them from.

Using previous history and activity to predict what they’re more likely to want.

Sending the right emails at the right times in the right formats.

Giving them potentially hyper-relevant suggestions.

Making them feel welcome.

All of this plays a part in doing that.

So, now, to achieve good sales, increase AOV, and improve customer retention, you will HAVE to personalize.

Relevantly and extensively.

Now that you know why, let’s get into the how.

There are so many ways you can go about this and so many things you can do here.

However, always look for things that:

1. Take the least effort to implement and 
2. Yield the best results.

For example, If you have multiple products, maybe redoing their pictures professionally as well as revamping the copy could help increase sales.

However, it’s equally likely that adding an upsell on the payment page eg. If someone bought a t=shirt, you could suggest “get this denim jacket as well, to complete the look” with a checkbox to easily add it without going anywhere else. That way, you potentially increase your sales as well.

However, that didn’t require NEARLY as much effort to implement and has the potential to increase sales as well.

So, try to start with the high-yield low-effort things then go from there.

That’s why, we’ll discuss three things:

1. Content personalization.
2. Product recommendations
3.  Email marketing personalization.

So. Content Personalization. Wut?

It all starts with data. 

The more data you have, from their location and their past purchase history (if applicable) to their browsing history and interests, the better-personalized content you’ll be able to create for them.

This includes presenting them with blog articles that they’ll like, targeted offers that they’re highly likely to explore, product recommendations, and sending them personalized emails.

When you visit a com website, you’re most likely there to buy or explore.

And, to keep you exploring and on the site, increasing your chances of adding something to the cart or even ending up buying something, that website needs to give you something of value.

A promo code, a flash sale, a special discount, free shipping, waiving the minimum order limit, whatever.

You need something relevant and valuable to YOU for them to be able to convince you to stay.

This goes even further, with “You might like” or “recommended for you” sections popping up while you explore various products…

suggested categories to help you further narrow down things while you’re searching, suggesting products that complement each other (ie suggesting a screen protector with a phone case), suggesting popular products, and much more.

Whatever content you have, from banners to pop-ups, and however much it can be personalized without making things irrelevant, do it.

And if you’re on the fence if it works or not, take this from Mckinsey:

“Our research shows that 71 percent of consumers expect companies to deliver personalized interactions.”

Mind-blowing, right?

71%! That’s nearly three-quarters!

All that effort is worth it, in the long run as well for the foreseeable future.

"Okay Drew. What’s next? Product recommendations? Didn’t we cover that?"

Nah, that was suggesting complementary products.

Here, it’s suggesting products that they’ll like.

So, suppose you have someone whose data implies that they’ll prefer things with muted, toned-down, and plain notes and colors, everything that you suggest…

From perfumes and caps to jackets and jeans…

Everything will be suggested accordingly.

I mean, you’re not going to recommend they buy a floral perfume with tangy citrus notes, right?

Instead, what you could do here is either recommend bundles of products (you know, like featured bundles or recommended products)...

Or just make sure they see things that align with their interests.

So, how this works is that, just like content personalization, you take in a lot of various data points.

Y’know, purchase history, browsing history, transaction data, website analytics, etc.

From there, implement recommendation algorithms to do the data analysis for patterns and trends (like frequently purchased items) and then generate personalized recommendations for the users.

Then, those can go in different sections, including "You may also like" or "Customers who bought this also bought" sections.

Then, it’s all about analyzing, optimizing, and tweaking things to make sure they perform well.

"Okay. That’s enough."

Actually, there’s just one more thing: Email marketing.

It’s really simple.

Now that you’ve done the effort and gone ahead and collected and analyzed various data to get suggestions and relevant content and personalize and…

All you need to do is use this in the emails you send out.

A good way to get their email is to use a pop-up that shows after they’ve spent a specific amount of time scrolling or browsing on your website and offer something, such as a discount or free shipping promo code.

That way, if they even end up leaving, you can still reach them through their email.

If someone leaves something in their cart instead of checking out and completing the payment technicalities…

There’s another opportunity to convert.

Personalized emails mean you can remind them, along with relevant recommendations to increase the chances of them returning.

In short, it’s about setting up personalized emails that trigger for specific reasons (such as cart abandonment, purchases, and sign-ups) and are sent at the right times with personalized offers (a discount off their cart or a reminder that their preferred product is going out of stock).

Just like product recommendations, this too requires optimization and refining to make things better and more effective

All in all though…

It’s not too hard to get started.

You’ve got the data coming in, start to collect and analyze it.

You’ve got the visitors coming in, start segmenting them based on various factors.

It’s all about using the right data in the right way to get the right person to buy the right thing.

Not simple.

But not too hard either.

And definitely worth it.

Anyways, this is a wrap. See you at the next one.

If you need help or would like my advice, I’d be more than happy to lend a helping hand. Feel free to reach out anytime and let’s work something out.

Till next time,

Drew out.