Web and mobile personalization at its best
With the help of many emerging AI and ML tools in the market, web personalization is becoming more versatile than ever. Mainly the tools are being used to tune contextual, user-specific personalization that increase user affinity for products/services.
My situation as an online shopper is somewhat like this, “I know what I need but not sure where to buy them…”
Over and above, most of the online shoppers experience a very similar perplexity.
And I know how much pain even purchasing a set of socks can cause if you are not a brand maniac.
Okay, take this: Balega running socks could fit the bill if yours are sweaty feet.
Continuing to how web personalization can heal the aforementioned agony, it is the process where you customize your website to the needs of a specific user (This will curtail the online shopping fatigue).
By using the insights you gain from analyzing user navigational behavior on your website. In correlation with other info accumulated in the form of structure, content and user profile data.
At best, the most practical steps to accomplish web personalisation are by
- Gathering web data
- Decision making
Gathering web data
There are two ways to collecting data on a user’s interest and activities on a website.
Implicit data:
“Users are not directly involved in the collection of implicit data”
This is the process of gathering information in specific to each user’s activities those are completed in the past. These data are recorded in web server logs.
Explicit data:
“Users apply the most effort in the collection of explicit data”
This information is obtained by users active involvement in the process of completing an event. For example, Email address submitted by a user during registration or a user rating an application in the apple store, demands the direct involvement of the user.
Step 1: Weed out unnecessary web data
The data obtained so far may appear somewhat trite and vague. Thus it is important to eliminate redundant information, such as removing the data retrieved from the web server, in the form of text files with a row for every HTTP transaction.
This data needs to be cleansed before analysis. By preprocessing this data we can filter out irrelevant information based on the goal of analysis.
Step 2: Deep learning web usage
Web mining or machine learning are the two techniques we could implement to discover the interesting web usage patterns. Collectively, these usage patterns may form the groups based on the users’ behavior.
By grouping content of a website into semantic categories, we can make the information retrieval and presentation easier for the user. This can also be done offline for automatic user profiling without adding the burden to the web server.
Decision making
After taking results of the previous analysis step, it is then time to perform recommendations to the users. These suggestions are given to the users by determining existing hyperlinks.
And relative to the last web page requested by the user, a new hyperlink can be inserted dynamically, that seem to be of interest for the current user. This step is generally accomplished by a variety of CGI programming.
Although with the excessive presence of information and services on the web, users have to spend their precious time for finding “right” or “interesting” information. But without proper guidance, a user often wanders aimlessly on irrelevant web pages, gains nothing, gets frustrated and leaves the site sooner than expected.
Therefore WWW began to foist new approaches of design and technology to let users consume information without a hitch. One such promising approach to solve this problem is web personalization.
How personalized website can augment more conversions?
Researching into what online shoppers think of web personalization, business2community have gotten a handful of stats…
- 45% of online shoppers are inclined to shopping on sites that recommend them based on their previous purchase activity.
- 53% of online shoppers think web personalization could ease their purchase journey.
- 57% of online shoppers are ready to give personal info if it would benefit them.
- 80% of diners are willing to choose from their personalized menu.
- 25% of the users are converting on the special offers displayed.
- Ads that are personalized convert more visitors than ordinary ads.
There are tons of best practices you can make use of to increase your website conversion. But here, let’s look at what good it has, to offer us.
Outwitting A/B testing:
There might be days in future where we would sit and laugh of how we ever took the time to do multiple A/B tests like a never ending process. To know how our users react to what we offered them then.
And to scrutinize and learn what visitors want or need. While this may rather come as a shock to hear from a company that offers testing suite. As of now, personalization seems limited to exit intent pop-ups and engines that recommend items based on users interest. And getting onto personalizing a website effectively, you must be able to select a specific set of user.
Then, offer them a variety of personalized items based on their previous interests. There are few tools that use machine learning to identify users usage patterns and to target items based on every user need. This will allow us to test faster with less traffic after all.
Delivering contextual content:
Showing contents relevant to users’ current context could nurture the more significant customer relationship. By tying up individual customer profiles to the real-time customer behavioral data, one can conceivably deliver, personalized data-driven content in the moment.
Having many such dynamic content tools available in the market, you can influence customer satisfaction by knitting a message to the moment and deliver accurate contextual marketing across all channels.
It does a whole lot of magic if every following page is made more relevant than the last, in simple: Change the experience as your users click through your website. And one best thing to do is, following up a customer service communication with a useful response.
Bonus: Send a very personalised message or give detailed information about the product that the user just abandoned in her cart.
Well, this is it.
The other powerful impacts of web personalization on conversion rates are getting baked in my forthcoming pieces.
Till then. CHEERS!