predict your customers
Anyone can build a product, but that is not the difficult part. The hard part is selling that product to the right customer at a desired price. There will always be a struggle on how to unfailingly attract a huge audience with seemingly unique needs.
Although a CMO and his team cannot charm their way to every target customer at all times, it can be argued that consumer behavior can be tracked and predicted to a certain degree. The traditional approach normally consists of long hours of non-scientific methods such as surveys and focus group discussions. Today however, the ongoing advancement of algorithms has astoundingly transformed how marketers can identify patterns in consumer behavior that will serve as the building blocks to compelling and effective campaigns. But first, what are algorithms?
what are algorithms?
In his TED Talk, David Malan said that “an algorithm is a method of solving problems both big and small”. He added that algorithms can be used in seemingly simple situations and also complex ones. In general, an “algorithm” denotes a sequence of rules designed to produce a specific outcome from a set of inputs. Illustratively, a food recipe is an algorithm for taking raw ingredients and turning them into a satisfying meal. Imagine a time when you googled a product, then switched to social media.
Chances are, the ads displayed on your feed were about the exact same product, or something that would complement it. Was there an occasion you delayed an online purchase, only to receive an email with that particular product on sale?
These scenarios might give goosebumps, but such is a result of complex algorithms designed to predict, and in some instances, even influence your behavior.
Companies can now easily retrieve and process exceptional amount of data using shopping and browsing preferences. Data can also be sourced and scraped from point-of-sale transactions, website traffic and social media posts. Predictive algorithms learn from this data to generate inferences about what is likely to happen in the future.
Just think of your favorite coffee shop. After a few visits in that said establishment, the barista would have already noticed that you always order cappuccino with skimmed milk. The coffee shop then uses this “data” to predict that tomorrow you will order the same thing, and have the coffee ready even before you get there. Predictive algorithms operate the same way but on a much bigger scale.
why are algorithms powerful?
Algorithms are everywhere. Search engine algorithms crawl over billions of potential website matches for an inquiry, and decide in milliseconds which ones to rank first. Social media algorithms determine which posts show up on a user’s curated feed; and video streaming algorithms can recommend shows and movies based on viewing history.
With the right data, algorithms can automate major strategic decisions at scale, lessen wasted spend, and maximize returns from every marketing activation ploy. While it is true that computers run these algorithms, it is human involvement and creativity that make the results of these algorithms truly impactful.
how to use algorithm
Below are some examples where algorithms are applied in modern marketing practices:
If structured well, algorithms can accept a complex decision and process it further to a set of recommended actions to take. (Picture a chess game, which uses artificial intelligence to suggest the next best move for any given situation.) A lot of marketing algorithms perform like this. For instance, an algorithm can capture behavioral data from hundreds of thousands of email interactions to identify the best time to send a business email that people will most likely open and read through
Today’s personalization tactics now go beyond demographics. An algorithm can process behavioral data to determine the target customer’s likely personality and choose the optimal creative to show, or product to offer from a set of choices
The link between a customer purchase and an earlier action—such as visiting a website or clicking a sponsored ad—can be intricate yet ambiguous. Algorithms can now draft a consumer’s path-to-purchase by getting engagement data from several campaigns and establish which touchpoints along the conversion path can be attributed to the actual purchase. Attribution models such as this tell critical information about the most effective channels, as well as those that give the least returns. Without sound attribution, marketers may wrongly assume a channel or campaign was ineffective when it actually worked great, or they may give too much credit to a touchpoint that had little to no effect on the end purchase decision.
algorithms, the future of marketing.
As algorithms continue to improve, they are becoming more profoundly embedded across all marketing channels. And as algorithms interrelate more closely with other algorithms, the overall level of automation also increases.
There is no denying that algorithms allow humans to arrive at better decisions faster, and leave more time for creative and value-adding activities. Consequently, CMOs will now always have a need to have his marketing team function alongside algorithms. In a similar way, the marketing team provides inputs that will secure that algorithms continue to perform as intended. Design Prodigy can make this synergy possible.
If you’d like to have a chat about how we make this happen at Design Prodigy, send us an email at email@example.com. Our growth marketers look forward to hearing from you.